Method, system, and computer program product for physician efficiency measurement and patient health risk stratification utilizing variable windows for episode creation

ABSTRACT

A method for measuring physician efficiency and patient health risk stratification is disclosed. Episodes of care are formed from medical claims data and an output process is performed. Physicians are assigned to report groups, and eligible physicians and episode assignments are determined. Condition-specific episode statistics and weighted episode statistics are calculated, from which physician efficiency scores are determined.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a Continuation of co-pending U.S. patent applicationSer. No. 13/621,234, filed Sep. 15, 2012, which is a Continuation ofU.S. patent application Ser. No. 13/012,219, filed Jan. 24, 2011, andissued as U.S. Pat. No. 8,340,981 on Dec. 25, 2012, which is aContinuation-in-part (CIP) of abandoned U.S. patent application Ser. No.12/769,090, filed Apr. 28, 2010, which is a Continuation of U.S. patentapplication Ser. No. 10/794,216, filed Mar. 5, 2004, and issued as U.S.Pat. No. 7,739,126 on Jun. 15, 2010, which claims the benefit of U.S.Provisional Patent Application Ser. No. 60/549,601, filed Mar. 2, 2004,all of which are hereby incorporated by reference in their entirety asif set forth herein.

BACKGROUND OF THE INVENTION 1. Field of the Invention

The present invention relates broadly to management of medicalinformation. More specifically, the present invention relates tomanagement of medical information to perform and report measurements ofphysician efficiency.

2. The Prior Art

Recent evidence has suggested that about 10-20% of physicians, acrossspecialty types, practice inefficiently. Efficient means using theappropriate amount of medical resources to treat a medical condition andachieve a desired health outcome. Thus, efficiency is a function of unitprice, volume of service, intensity of service, and quality of service.This group of inefficient physicians is responsible for driving 10% to20% of the unnecessary, excess medical expenditures incurred byemployers and other healthcare purchasers, equating to billions ofdollars nationally.

To improve market efficiency, it is useful to apply a system thataccurately measures individual physician efficiency. Recent evidence hasdemonstrated that leading physician efficiency measurement systems haveonly about 15-30% agreement across measurement systems. This means thatwhen one system ranks a physician as inefficient, only about 15-30% ofthe other systems ranked the same physician as inefficient. Theremaining 70% (or more) of systems ranked the same physician asefficient.

These findings show that existing systems have significant error inattempting to accurately identify inefficient physicians. The errorneeds to be eliminated, or significantly reduced, if healthcarepurchasers are to accurately identify inefficient physicians and takeaction (e.g., attempt to change physician behavior, provide incentivesfor employees to use more efficient physicians). Every physician falselymeasured as efficient (or inefficient) leads to continued inefficiencyin the healthcare marketplace.

There are ten common physician (or physician group) efficiencymeasurement errors present in most existing physician efficiencymeasurement systems, which are in order of importance: (1) examine allepisodes of care for a physician; (2) use a physician's actual episodecomposition; (3) no severity-of-illness measure by medical condition;(4) no identification of different episode treatment stages; (5) no agecategory assignment by medical condition; (6) no tracking mechanism forrelated complication episodes; (7) improper episode outlier criteria;(8) under-report charges attributed to partial episodes; (8) over-reportcharges attributed to episode endpoints; and (10) no minimum number ofepisodes of care. These errors are discussed next.

Many physician efficiency methodologies continue to examine “servicesper 1,000 members” or “all episodes of care” tracked to a physician.These approaches probably add the most to efficiency measurement error.The methodologies attempt to adjust services per 1,000 members and toadjust all episodes of care by age and gender—and then compare onephysician's utilization pattern to a peer group average. However, ageand gender explain less than 5% of the variance in a patient's medicalexpenditures. This means that over 95% of the variance is unexplained,and may be attributed to differences in patient health status.

Some methodologies adjust services per 1,000 members and adjust allepisodes of care based on specific International Clinical Modificationof Diseases ninth edition (ICD.9) code algorithms that measure expectedresource intensity. The idea is that a patient's diagnosis codes willprovide more predictive power than age and gender alone. The mostpredictive of the published and marketed models explain only 20% to 30%of the variance in a patient's medical expenditures. This means that 70%or more of the variance continues to be unexplained, and may beattributed to differences in patient health status.

Physicians often criticize the services per 1,000 members and the allepisodes of care methodologies that use a predictive case-mix adjustmentfactor. Physicians state that the methodologies do not appropriatelyadjust for differences in patient health status—rightly stating thattheir patients may be “sicker.”

If all claim line items (CLIs) or episodes of care tracked to aphysician are used in the efficiency analysis, then up to 70% of theobserved utilization difference between physicians may be attributed topatient health status differences. Therefore, patient health statusdifferences are measured rather than individual physician efficiencydifferences. This weakness in current case-mix adjustment tools meansthat not all CLIs or patient episodes of care treated by a physician canbe examined. Instead, an isolated set of more prevalent medicalconditions by severity-of-illness level needs to be examined acrossphysicians of a similar specialty type.

The second measurement error, which occurs in most if not all currentefficiency measurement systems, occurs when the physician's actualepisode composition is used. The reason is as follows. The differencesin physicians' patient case-mix composition results in differences invariability (i.e., the standard deviation) around a physician's averageepisode treatment charges. This variability is not due to the efficiencyor inefficiency of a physician, but instead results because longer andmore resource-intensive medical conditions generally require moreservices and, therefore, have more potential variability around average(or mean) episode treatment charges.

For example, easier-to-treat upper respiratory infection (URI) episodesmay have the following mean and standard deviation (with outlierepisodes removed): $185±$65. Here, the standard deviation around themean is not large—and is 0.35 the size of the mean (i.e., 65/185=0.35).However, easier-to-treat pediatric asthma episodes may have thefollowing mean and standard deviation (with outlier episodes removed):$1,650±$850. Here, the standard deviation around the mean is larger thanfor URI episodes—and is 0.52 the size of the mean (i.e.,850/1,650=0.52).

The variation difference between the two conditions is 49% greater forasthma than URIs_[(0.52−0.35)/0.35]. This variation difference occursfor two reasons: (1) more resource-intensive conditions require moreservices to treat; and (2) there generally are a small number ofepisodes available to examine in a given physician efficiency study ascompared to the universe of episodes that could actually be studied—anda smaller number of episodes results in a higher chance for variabilityaround the mean. This variation is not the result of physician treatmentpattern differences.

If the statistically based variability around the mean is not corrected,then substantial error may enter into the physician efficiencymeasurement equation. Consequently, the final physician efficiency scoredifferences may be attributed to the statistical condition-specificvariability around the mean episode charge (due to the case-mix ofepisodes treated).

The above example showed that the variation difference may be 50% ormore (around a condition-specific mean episode value). Logically, then,if all episodes treated by physicians are examined and efficiency scoresare calculated, there has to be some statistical bias present.

A significant statistical bias may be present. Using a more traditionalepisode-based efficiency measurement methodology, lower-episode-volumephysicians treating patients with a higher case-mix index score are morelikely to receive an inefficient ranking as compared tolower-episode-volume physicians treating patients with a lower case-mixindex score. This finding results because a physician with highercase-mix patients treats episodes having more variability (i.e., agreater standard deviation) around average episode treatment charges.With a low volume of episodes (most often the norm, and not theexception), this physician needs only a few higher-cost episodes thenthe peer group average to make his/her treatment pattern appearsignificantly higher than the peer group comparator.

However, a physician with lower case-mix patients treats episodes havingless variability around average episode treatment charges. With a lowvolume of episodes, this physician's treatment pattern will not be asinfluenced by one or two higher-cost episodes as compared to the peergroup average. Consequently, his/her treatment pattern does not appear(as often) significantly higher than the peer group comparator.

Thus, by examining all medical condition episodes, a substantialcomponent of any observed physician efficiency difference may beattributed to statistical condition-specific variability around the meanepisode charge—and not to physician treatment patterns efficiency. Thiseffect may be present even when we examine the easier-to-treat episodes(SOI-1 level episodes) for the medical conditions.

The third error takes place in those efficiency measurement systems thatdo not employ an appropriate episode severity-of-illness measure.Severity-of-illness may be defined as the probability of loss offunction due to a specific medical condition. Most, if not all, currentclaims-based episode groupers and methods do not have an appropriateseverity-of-illness index by medical condition. Consequently,significant clinical heterogeneity remains in many episodes for a givenmedical condition. The end result may be physician efficiencydifferences that are attributed to inaccurate episodeseverity-of-illness adjustment, and not to physician treatment patternsvariation.

Moreover, some claims-based episode groupers stratify formulatedepisodes for a medical condition by the presence or absence of aspecific surgery or service (e.g., knee derangement with and withoutsurgery; ischemic heart disease with and without heart catheterization).The reason for performing this stratification is to reduce episodeheterogeneity for a medical condition. In effect, the stratificationserves as a sort of severity-of-illness adjustment.

However, stratification based on the presence of surgery or a high-costservice results in at least two physician efficiency measurement errors:(1) performing surgery versus not performing surgery is the treatmentpatterns variation we need to examine in determining physicianefficiency, and this variation is not captured in more traditionalmethodologies; and (2) the episodes of care are unnecessarily separatedinto smaller groups whereby physicians may not have enough episodes toexamine in any one smaller group. Consequently, the stratified episodesof care need to be recombined for accurate physician efficiencymeasurement.

The fourth physician efficiency measurement error occurs in claims-basedepisode groupers do not have a method for identifying different episodetreatment stages including initial, active, and follow-up treatmentstages. Identifying different treatment stages is important in medicalconditions, such as breast cancer, prostate cancer, colorectal cancer,acute myocardial infarction, and lymphoma. For example, breast cancershould be stratified into initial, active, and follow-up treatmentstages.

An initial breast cancer episode is one where the patient has a surgeryfor the cancer (e.g., lumpectomy, modified radial mastectomy). An activebreast cancer episode is one where no surgery is present, butchemotherapy or radiation treatment is observed within the episode.Here, the patient underwent surgery in a previous study period, so nosurgical event is found in the patient's current ongoing breast cancerepisode. Instead, during the study period, the claims data shows thatthe patient is being treated with chemotherapy and/or radiation. Thepresence of these treatments defines an active breast cancer episode.The utilization pattern and charges are different for an active breastcancer patient as compared to an initial breast cancer patient. Afollow-up breast cancer episode is one where no surgery, chemotherapy,or radiation treatment is present in the patient's episode of care.After initial and active treatments, physicians will continue to codefor breast cancer over the future years of patient follow-up care.

In a given study period, physicians do not treat an equal distributionof each episode type (initial, active, and follow-up). Moreover, theepisode types have different average charges. About 20% of episodes maybe classified as initial breast cancer episodes. Overall care forinitial breast cancer episodes ranges between $15,000 and $25,000 perepisode. About 15% of episodes may be classified as active breast cancerepisodes. Overall care for active breast cancer episodes ranges between$12,000 and $18,000 per episode. About 65% of episodes may be classifiedas follow-up breast cancer episodes. Overall care for follow-up breastcancer episodes ranges between $350 and $600 per episode.

Consequently, the blending of the three treatment stage episodes resultsin average treatment charges of about $5,500 to $6,500 per episode. Infact, this is the average breast cancer charge that would be observedfor most claims-based episode groupers.

The blending of initial, active, and follow-up episodes may lead tosubstantial physician efficiency measurement error. For example, assumeduring a study period that Oncologist A treats mostly active breastcancer patients, while some other oncologists have a good mixture ofactive and follow-up patients. Then, Oncologist A's treatment patternfor breast cancer will appear inefficient (as compared to his peer groupof oncologists) because active episodes are about 30 times moreexpensive to treat than follow-up episodes. In fact, Oncologist A'streatment pattern difference is attributed to a different treatmentstage episode case-mix.

Therefore, treatment stage episode types need to be correctly identifiedand separately examined. Otherwise, the final physician efficiency scoredifferences may be attributed to nothing more than the initial, active,and follow-up episode case-mix.

The fifth error happens in those physician efficiency measurementsystems that do not examine condition-specific episodes by age category.Studies have illustrated that broad-based age bands are important toseparately examine—even after episodes have been assigned aseverity-of-illness index. The reason is that physicians tend to treatchildren and adults differently for most conditions. For example,children are less likely than adults to receive a chest x-ray and potentantibiotics for many medical conditions. If episodes are not examined bybroad-based age category, the end result may be physician efficiencydifferences that are attributed to patient age differences—and not totreatment patterns variation.

The sixth error occurs in those physician efficiency measurement systemsthat do not link and include the charges and utilization from apatient's complication episodes to his underlying medical condition.Complications are those episodes that are clinically related to theunderlying medical condition. Consequently, many condition-specificepisodes have under-reported charges. In fact, actual outputs from someclaims-based episode groupers may show under-reported charges forpatients with diabetes and other chronic conditions (e.g., asthma,congestive heart failure).

For example, the reason for the under-reported episode charges is thatphysicians code up to 70% of an average diabetic's charges under relatedcomplications to the diabetes (e.g., eye, neuropathies, circulatory,renal) and not diabetes care. Therefore, without considering andincluding related complication episodes with the actual diabetesepisode, physician efficiency differences may be attributed toincomplete episode charges and utilization—and not to treatment patternvariations.

Furthermore, for patients with specific medical conditions, any modelthat attempts to stratify patients by health risk may produce unstableor erroneous results. The reason is that a patient is missing key claimsinformation needed to accurately classify a patient into an appropriateseverity-of-illness and other classes. For example, without trackingrelated complications to a diabetic patient, many diabetic patients willappear to have no complications when in fact they have eye orcirculatory complications.

The seventh physician efficiency measurement error happens when thecondition-specific outlier episode analysis is not performed in anappropriate manner. Many current methodologies perform the high-endoutlier analysis by eliminating a percent of condition-specific episodesat the peer group (or aggregate episode) level. That is, themethodologies eliminate the high-end outliers before assigning episodesto physicians.

However, this method results in physician efficiency measurement errorbecause a higher proportion of episodes assigned to the most inefficientphysicians will be eliminated (as compared to the proportion of episodeseliminated for efficient physicians). Consequently, the inefficientphysicians' condition-specific treatment patterns now more closelyresemble the treatment patterns of the efficient physicians.

An example demonstrates this error. Assume Physician A has sevenepisodes of acute bronchitis with the following per episode charges:$235, $245, $325 $400, $525, $550, and $600. Also, the outlier cut-offthreshold for high-end outlier episodes is set at $399 at the peer grouplevel. Physician A now has only three episodes remaining at $235, $245,$325. The mean charge is $268 per episode. Assume Physician B also has 7episodes of acute bronchitis with the following per episode charges:$210, $225, $235, $255, $285, $320, and $390. The peer-group leveloutlier threshold remains at $399. Therefore, Physician B has all sevenepisodes remaining, and the mean charge is $274.

The end result shows no statistical difference between Physicians A andB. The mean episode charge of Physician A is slightly lower thanPhysician B (i.e., $268 versus $274 per episode). However, using anoutlier rule where we eliminate 5% of episodes (or at least 1 high-endoutlier) are eliminated at the physician level, the results aresignificantly different. Physician A now has six remaining episodes(i.e., here we eliminate only 1 high-end outlier), and the mean chargeof the six non-outlier episodes is now $380 per episode. For PhysicianB, the mean charge for the six non-outlier episodes is now $255 perepisode. Physician A is statistically higher in average (or mean)episode charges than Physician B by $125 per episode.

The eighth error occurs in those systems that under-report chargesattributed to partial (or incomplete) episodes of care. Somemethodologies do not separate partial from complete episodes of carewhen measuring physician efficiency. Partial episodes result because apatient enrolled in a health plan during the study period or disenrolledduring the study period. However, including partial episodes leads toinaccurate efficiency measurement because of under-reported episodecharges—especially when some physicians have more partial episodes thanother physicians.

A reason partial episodes often slip through the cracks and into anefficiency analysis is because the methodologies do not use a membershipeligibility file to ensure the member is present for the entire studyperiod. Instead, the methods assume that a condition-specific episode ofcare is complete if the episode exceeds some minimum duration timeperiod. For example, if a patient's episode of diabetes is 40 days ormore in duration, then the episode is marked as complete—and notpartial. If a patient's diabetes episode is 39 days or less, then theepisode is marked as partial.

Applying an indiscriminate time period duration to condition-specificepisodes produces a high percentage of episodes marked as complete,which are actually partial (or incomplete) episodes. That is, manyhealth plan's have membership turnover rates of 20% or higher.Consequently, a diabetes episode of 40 days duration—marked ascomplete—has at least a 20% chance of being a partial episode of carebecause of membership turnover. The end result may be physicianefficiency differences that are attributed to the inclusion of partialepisodes—and not to treatment patterns variation.

The ninth error happens in physician efficiency measurement systems thatover-report charges attributed to episode endpoints. Some methodologiesdo not appropriately end a patient's episode of care before measuring aphysician's efficiency. For example, chronic conditions may continueindefinitely and, therefore, patient episodes of care may be of variousdurations (e.g., 60 days or 600 days)—depending on the amount ofavailable patient claims data. The end result may be physicianefficiency differences that are attributed to excessively long orvariable chronic condition episode durations—and not to treatmentpatterns variation.

The tenth error takes place in those systems that impose fewrequirements for having a minimum number of episodes in a certain numberof medical conditions. Many methodologies do not require a minimumnumber of condition-specific episodes when comparing a physician'sefficiency to a peer group. Instead, only a small handful (e.g., lessthan 10 episodes) are enough. However, there may be significant episodeof care heterogeneity in one or two condition-specific episodes—evenafter applying a sophisticated severity-of-illness index. Consequently,examining an episode here-and-there for a physician may introducesignificant error into a physician's efficiency measurement. The endresult may be physician efficiency differences that are attributed tothe heterogeneity in the low number of episodes examined—and not totreatment patterns variation.

Various systems have been patented in the episode of care field. Suchsystems are shown, for example, in U.S. Pat. Nos. 5,557,514, 5,835,897and 5,970,463. However, none of these systems adequately overcome theaforementioned problems with respect to appropriately building andanalyzing episodes of care. As importantly, existing systems fail todiscuss an episode-of-care-based system for measuring individual orphysician group efficiency measurement.

BRIEF SUMMARY OF THE INVENTION

In one aspect, the present invention provides a method of determiningphysician efficiency. The method comprises: obtaining medical claimsdata; performing patient analysis using the obtained medical claims datato form episodes of care; performing output process based on performedpatient analysis, the output process comprising at least one actselected from the group consisting of: eliminating partial episodes ofcare and episodes of care marked with comorbidities; assigning episodesto physicians; grouping claim line items in episodes to servicecategories; and applying a maximum duration rule to episodes of care;assigning at least one physician to a report group; determining eligiblephysicians and episode assignments by performing at least one actselected from the group consisting of: eliminating physicians from thereport group, the eliminated physicians having specialties that are notassigned to a grouping of medical conditions that account for someepisodes treated by a physician having a specialty type; eliminatingphysicians that are not in a report group of interest; and eliminatingepisode assignments not meeting a selected criterion; calculatingcondition-specific episode statistics; calculating weighted episodestatistics across medical conditions; and determining efficiency scoresfor physicians from the calculated condition-specific episode statisticsand the weighted episode statistics calculated across medicalconditions.

In an embodiment, the act of calculating condition-specific episodestatistics comprises calculating condition-specific episode statisticsfor physicians in the report group. In an embodiment, the act ofcalculating condition-specific episode statistics comprises calculatingcondition-specific episode statistics for peer groups. In an embodiment,the act of calculating weighted episode statistics comprises calculatingpeer group weighted episode statistics across medical conditions. In anembodiment, the act of calculating weighted episode statistics comprisescalculating physician weighted episode statistics across medicalconditions.

In another aspect, the present invention provides a computer programproduct tangibly embodied in computer instructions which, when executedby a computer, determine physician efficiency. The computerinstructions, when executed, perform the acts of: obtaining medicalclaims data; performing patient analysis using the obtained medicalclaims data to form episodes of care; performing output process based onperformed patient analysis, the output process comprising at least oneact selected from the group consisting of: eliminating partial episodesof care and episodes of care marked with comorbidities; assigningepisodes to physicians; grouping claim line items in episodes to servicecategories; and applying a maximum duration rule to episodes of care;assigning at least one physician to a report group; determining eligiblephysicians and episode assignments by performing at least one actselected from the group consisting of: eliminating physicians from thereport group, the eliminated physicians having specialties that are notassigned to a grouping of medical conditions that account for someepisodes treated by a physician having a specialty type; eliminatingphysicians that are not in a report group of interest; and eliminatingepisode assignments not meeting a selected criterion; calculatingcondition-specific episode statistics; calculating weighted episodestatistics across medical conditions; and determining efficiency scoresfor physicians from the calculated condition-specific episode statisticsand the weighted episode statistics calculated across medicalconditions.

In an embodiment, the act of calculating condition-specific episodestatistics comprises calculating condition-specific episode statisticsfor physicians in the report group. In an embodiment, the act ofcalculating condition-specific episode statistics comprises calculatingcondition-specific episode statistics for peer groups. In an embodiment,the act of calculating weighted episode statistics comprises calculatingpeer group weighted episode statistics across medical conditions. In anembodiment, the act of calculating weighted episode statistics comprisescalculating physician weighted episode statistics across medicalconditions.

In yet another aspect, the present invention provides a system fordetermining physician efficiency. The system comprises means forobtaining medical claims data; means for performing patient analysisusing the obtained medical claims data to form episodes of care; meansfor performing output process based on performed patient analysis, theoutput process comprising at least one act selected from the groupconsisting of: eliminating partial episodes of care and episodes of caremarked with comorbidities; assigning episodes to physicians; groupingclaim line items in episodes to service categories; and applying amaximum duration rule to episodes of care; means for assigning at leastone physician to a report group; means for determining eligiblephysicians and episode assignments by performing at least one actselected from the group consisting of: eliminating physicians from thereport group, the eliminated physicians having specialties that are notassigned to a grouping of medical conditions that account for someepisodes treated by a physician having a specialty type; eliminatingphysicians that are not in a report group of interest; and eliminatingepisode assignments not meeting a selected criterion; means forcalculating condition-specific episode statistics; means for calculatingweighted episode statistics across medical conditions; and means fordetermining efficiency scores for physicians from the calculatedcondition-specific episode statistics and the weighted episodestatistics calculated across medical conditions.

In an embodiment, the means for calculating condition-specific episodestatistics comprises means for calculating condition-specific episodestatistics for physicians in the report group. In an embodiment, themeans for calculating condition-specific episode statistics comprisesmeans for calculating condition-specific episode statistics for peergroups. In an embodiment, the means for calculating weighted episodestatistics comprises means for calculating peer group weighted episodestatistics across medical conditions. In an embodiment, the means forcalculating weighted episode statistics comprises means for calculatingphysician weighted episode statistics across medical conditions.

In yet another aspect, the present invention provides a method ofperforming patient health risk stratification, the method comprising:obtaining medical claims data; performing patient analysis using theobtained medical claims data to form episodes of care; and performingoutput process based on performed patient analysis, the output processcomprising at least one act selected from the group consisting of:eliminating partial episodes of care and episodes of care marked withcomorbidities; assigning episodes to physicians; grouping claim lineitems in episodes to service categories; and applying a maximum durationrule to episodes of care.

In yet another aspect, the present invention provides a computer programproduct tangibly embodied in computer instructions which, when executedby a computer, performs patient health risk stratification. The computerinstructions, when executed, perform the acts of: obtaining medicalclaims data; performing patient analysis using the obtained medicalclaims data to form episodes of care; and performing output processbased on performed patient analysis, the output process comprising atleast one act selected from the group consisting of: eliminating partialepisodes of care and episodes of care marked with comorbidities;assigning episodes to physicians; grouping claim line items in episodesto service categories; and applying a maximum duration rule to episodesof care.

In yet another aspect, the present invention provides a system forperforming patient health risk stratification. The system comprises:means for obtaining medical claims data; means for performing patientanalysis using the obtained medical claims data to form episodes ofcare; and means for performing output process based on performed patientanalysis, the output process comprising at least one act selected fromthe group consisting of: eliminating partial episodes of care andepisodes of care marked with comorbidities; assigning episodes tophysicians; grouping claim line items in episodes to service categories;and applying a maximum duration rule to episodes of care.

Additional features and advantages of the present invention will berealized by one skilled in the art upon reading the following detaileddescription, when considered in conjunction with the accompanyingdrawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a drawing that illustrates, in flow diagram form, functionalaspects of the present invention.

FIG. 2 is a flowchart that illustrates, in flow diagram form, a sequenceof acts executed in accordance with embodiments of the presentinvention.

FIG. 3 is a drawing that illustrates a dynamic window period utilized indefining the duration of an acute episode of care in accordance withembodiments of the present invention.

FIG. 4 is a drawing that illustrates a static window period utilized indefining the duration of an acute episode of care in accordance withembodiments of the present invention.

FIG. 5 is a drawing that illustrates a variable window period utilizedin defining the duration of an acute episode of care in accordance withembodiments of the present invention.

FIG. 6 illustrates, in flow diagram form, a sequence of acts executed toperform a vertical merge rule function in accordance with embodiments ofthe present invention.

FIG. 7 illustrates, in flow diagram form, a sequence of acts executed toperform a horizontal merge rule function in accordance with embodimentsof the present invention.

FIG. 8 illustrates, in tabular form, a Practitioner EfficiencyMeasurement Report 1, detailing average charges per episode of care.

FIG. 9 illustrates, in tabular form, a Practitioner EfficiencyMeasurement Report 2, detailing average utilization per episode of care

DETAILED DESCRIPTION

Step A: Utilize Claims Data File

Medical claims data is utilized in an embodiment of the presentinvention, and generally consists of a family, member, claim, and claimline item (CLI) structure. A claim generally consists of one or moreCLIs. The claims data consists of medical events that are incurred bythe patient visiting a healthcare professional or a facility in theambulatory, outpatient, inpatient, home, and other environments wheremedical services may be delivered.

Step B: Extract Core Claims Data Fields

In order to form longitudinal episodes of care, assign them tophysicians, and analyze individual physician efficiency, medical claimsdata must be mapped to the system requirements of the present invention.The process maps medical claims by performing field mapping and fieldvalue mapping. In field mapping, fields in the source data areidentified that correspond to each of the required fields. In fieldvalue mapping, for each field where applicable, the user determines thefield value that corresponds to each possible value that may occur inthe source data.

Five types of data are mapped: client-defined codes, value fields,dates, system-specific codes, and standard codes. The present inventionuses client-defined codes for physicians and members. Value fieldsinclude dollar amount, counts, and similar numeric data according tospecified value formats. Calendar dates are mapped according to thespecified standard format. System-specific codes include provider type,place of service, physician specialty, type of service, and similarcodes. Standard codes include CPT codes, ICD.9 procedural codes, andsimilar codes.

A record refers to a CLI. The mapped claims file consists of one outputrecord for each record in the source data, except those that areduplicates resulting from adjudication process. The field byte size isnoted in Table 1 below. Each record is terminated by a one byteend-of-line character.

The present invention uses the fields in the following table. Mandatoryfields must be filled for all records in the order listed for correctfunctionality of the present invention. Non-mandatory fields areoptional.

TABLE 1 CLI Mapping Code Fields Mandatory Field or Non- Number Type Name& Description Format mandatory 1 1 Primary subscriber identifier. Thesubscriber number 15 char M used to identify a family unit. 2 1 Memberidentifier. The unique identifier of a person 15 char M within a family.The field value should uniquely identify an individual when combinedwith the primary subscriber identifier (field #1). 3 3 Claim start date.Date of first service on a claim. 8 date NM yyyymmdd 4 3 Claim end date.Date of last service on a claim. 8 date NM yyyymmdd 5 — Not applicableto commercial market. 15 char — 6 5 Subscriber's mailing address. Thezip code of the 15 char NM subscriber's address. 7 4 Gender code. Thegender for this CLI. 1 char, enum NM 8 4 Race code. The race identifierfor this CLI. 1 char, map NM 9 3 Member's date of birth. The date ofbirth for the member 8 date M on this CLI. The entry in this field isused to calculate the yyyymmdd member's age. 10 4 Member status code.The entry in this field is used to 2 char M identify members who will beanalyzed. Once a study Field must = population is identified, eachmember should be 10 for assigned a value of 10 in this field. Otherwise,the member to member will not be processed. be processed 11 1 Referringprovider identifier. Defines the provider that 15 char NM referred amember to another provider that generated the specific claim ofinterest. 12 5 Procedure code year. The year that a specific CPT-4, 1char NM HCPCS, UB-92, or ICD.9 procedure code was used on a claim. 13 —Not applicable to commercial market. 3 char — 14 — Not applicable tocommercial market. 20 char — 15 1 Performing provider identifier. Thisfield refers to the 15 char M provider that billed for the specific CLI.16 4 Provider type code. The type of billing entity that 1 char, map Mdelivered the service for this CLI. 17 4 Physician specialty code. Thespecialty under which the 2 char, map M physician or other health careprofessional delivered the service for this CLI when delivered forpayment. 18 — Not applicable to commercial market. 1 char — 19 — Notapplicable to commercial market. 1 char — 20 2 Line item service count.The number of services 4 char M performed on a specific CLI. 21 — Notapplicable to commercial market. 1 char — 22 4 Place of service code.The place where the unique 2 char, map M service of this line item wasrendered to the patient. 23 3 Claim line item (CLI) start date. Thisfield refers to the 8 date M date of the first service on a CLI yyyymmdd24 3 CLI end date. Date of last service on a CLI. 8 date M yyyymmdd 25 5Procedure code. The specific CPT-4, HCPCS, ICD.9 5 char M procedure,UB-92, and other procedure codes used to identify a specific service. 265 Initial procedure code modifier. Used to add an initial 2 char NMmodifier to a procedure code. 27 5 Second procedure code modifier. Thisfield is used to 2 char NM add a second modifier to a procedure code. 284 BETOS Code. Every CLI processed by the system 3 char M expect thosesubmitted on UB-92 forms must have a BETOS code. 29 5 National drugcode. The national drug code (NDC) that 11 char NM identifies a specificprescription drug by product name, formulation, and quantity. 30 — Notapplicable to commercial market. 7 char — 31 2 Allowed charge amount.The allowed charge amount, 10 char M often referred to the coveredcharge amount. Allowed charges typically equal submitted charges minusineligible charges and discounts. They include (are the sum of) paid,copay/deductible/coinsurance, and COB. 32 — Not applicable to commercialmarket. 2 char — 33 — Not applicable to commercial market. 1 char — 34 5CLI diagnosis code. The primary ICD.9 diagnosis code 5 char M on a CLI.35 4 Detailed grouping code. A detailed grouping code is a 15 char NMclient-specified identifier that is the base data element aggregatedtogether to form a report group. For example, zip codes or taxidentification numbers could be detailed grouping codes. 36 5 SecondaryCLI diagnosis code. The secondary ICD.9 5 char NM diagnosis code on aCLI. 37 5 Tertiary CLI diagnosis code. The tertiary ICD.9 diagnosis 5char NM code on a CLI.

Provider type codes (Field 16) identify the type of billing entity thatdelivered a service to a patient. The defined provider types are: none,physician, facility, pharmacy, independent service provider, and other.For none, no provider type is identified. Physicians are professionalsdelivering medical care services, not just physicians. This providertype includes physicians, chiropractors, acupuncturists, podiatrists,nurse practitioners, physical therapists, and other professionalsdelivering medical care services. Facility includes hospital inpatient,hospital outpatient, long term nursing homes, intermediate nursinghomes, skilled nursing homes, rehabilitation facilities, end-stage renaldisease facilities, and similar facilities. Pharmacy includes walk-in ormail-order pharmacies. This provider type is used by the presentinvention to identify the use of a prescription drug. Independentservice providers include providers that are not associated with afacility or a physician's office, such as independent laboratories andimaging centers. Typically, an independent service provider deliversservices that, depending on physician office capabilities, could beprovided in a physician's office directly. Other is healthcare servicessuch as durable medical equipment providers, medical supply providers,ambulance, home meal delivery, and other similar providers. Table 2shows the provider type codes.

TABLE 2 Provider Type Codes Provider Type Code None 0 Physician 1 (Thisvalue is not applicable to 2 commercial populations.) Facility 3Pharmacy 4 Independent service provider 5 Other 6Table 3 shows physician specialty codes (Field 17).

TABLE 3 Physician Specialty Codes Specialty Code None (Use this codewhen physician 0 is not the provider type) Allergist 1 AlliedPractitioner 2 Anesthesiology 3 Anesthesiology Assistant 4 Cardiology 5Cardiothoracic surgery 6 Chiropractor 7 Dermatology 8 Emergency Medicine9 Endocrinology 10 Family/General Practice 11 Gastroenterology 12General Internist 13 General surgery 14 Genetic 15 Infectious Disease 16Neonatal Care 17 Nephrology 18 Neurology 19 Neurosurgery 20Obstetrician/Gynecologist 21 Oncology/Hematology 22 Ophthalmology 23Optometry 24 Oral-maxillofacial Surgeon 25 Orthopedist 26 Otolaryngology(ENT) 27 Pain management 28 Pathology 29 Pediatrics 30 Plastic surgery31 Podiatry 32 Psychiatry 33 Psychologist 34 Psychology Professional(e.g., social worker) 35 Pulmonology 36 Radiology 37 Rheumatology 38Sports and physical medicine 39 Urology 40 Vascular surgeon 41 Criticalcare 42 Other 99

The place of service code identifies where a unique service was providedto a patient (e.g., office, outpatient facility of a hospital, inpatientfacility of a hospital). Table 4 shows the place of service codes (Field22)

TABLE 4 Place of Service Codes Place of Service Code Description None 0No place of service code or unknown place of service. Office 1 Servicedelivered in a physician's office. Home 2 Service delivered in apatient's home environment. Emergency room 3 Service delivered in theemergency room department of a hospital. Urgent care facility 4 Servicedelivered in an urgent care facility. Inpatient hospital 5 Inpatientservice delivered in a hospital. Outpatient hospital 6 Outpatientservice delivered in a hospital. Ambulance 7 Service delivered in aland, air or water ambulance. Ambulatory surgical 8 Service delivered ina walk-in surgical center center. Birthing center 9 Service delivered ina birthing center. Military treatment 10 Service delivered in a militarytreatment facility facility. Inpatient psychiatric 11 Service deliveredon an inpatient basis at a facility psychiatric facility for mentalhealth or chemical dependency. Public health clinic 12 Service deliveredin a state or local public health clinic or a rural health clinic.Independent 13 Service delivered at an independent laboratorylaboratory. Alternative care 14 Service delivered in an alternate carefacility facility such as a skilled nursing facility, nursing facility,custodial care facility, hospice, adult living care facility (ACLF),psychiatric facility partial hospitalization, community mental healthcenter, intermediate care facility/mentally retarded, residentialsubstance abuse treatment facility, psychiatric residential treatmentcenter, comprehensive inpatient rehabilitation facility comprehensiveoutpatient rehabilitation facility, end stage renal disease treatmentfacility, or similar facilities. Other ambulatory 15 Service deliveredin a walk-in facility environment such as a school, homeless shelter,health center, immunizations center, or similar facility. Mobile unit 16Service delivered in a unit that brings specific services tocommunities. Other 17 Other places of service not included in the typeslisted in this table. Pharmacy 18 Indicates that the prescription drugwas dispensed by a walk-in or mail-order pharmacy. This includeshospital-run pharmacies that may dispense prescription drugs on anoutpatient basis.Type of Service (BETOS) Codes (Field 28)

In an embodiment, the present invention uses BETOS (Berenson-Eggers typeof service) Codes as the type of service code (Field 28). The BETOS Codesystem is a procedure code system that organizes procedures and servicesinto groupings that have been generally accepted as clinicallymeaningful. The BETOS Code system categories allow objective assignmentof procedures and services. A BETOS Code must be assigned for eachservice on a CLI (e.g., CPT-4, HCPCS), except those submitted on UB-92forms. Any homegrown codes or other special service codes that do nothave BETOS Code must be mapped to a specific BETOS Codes.

In an embodiment, the present invention groups all health services witha BETOS Code into one of 11 service categories. Moreover, an embodimentof the present invention also groups all health services with a BETOSCode into one of 21 sub-service categories. Services without a BETOSCode will be assigned to our other medical services category. In anembodiment, alternative CLI health services grouping system may beapplied other than BETOS codes.

The services provided during an episode of care are separated into thefollowing 11 service categories and 21 sub-service categories presentedbelow.

Category 0 is the overall results in the output files. The overallresults are normally presented in the 0 row or the 0 section of theoutput file. This category captures the overall information for aphysician. In an embodiment, the present invention calculates overallcharges, but does not calculate overall utilization. As a result, theoverall utilization entry 0 row is used to present the average duration(in days).

The professional visits (prof visits) service category presents chargesand utilization for professional visits incurred in the physician'soffice, clinic or outpatient department of a hospital. For utilization,the numerator unit is visits. The sub-service category also isprofessional visits. This sub-service category presents charges andutilization for professional visits incurred in the physician's office,clinic, or outpatient department of a hospital.

The diagnostic tests (diag tests) service category presents charges andutilization for diagnostic tests incurred in the physician's office,clinic, outpatient department of a hospital, or surgicenter. Diagnostictests represent imaging tests (X-rays, CAT scans, MRIs, etc.),functional tests (EKGs, echocardiograms, etc.), and invasive tests.There are three sub-service categories for diagnostic testing. The firstsub-service category is imaging tests. This sub-service categorypresents charges and utilization for imaging tests, which includex-rays, CAT scans, MRI, and other related imaging tests. For utilizationthe numerator unit is services or tests. The second sub-service categoryis invasive testing. This sub-service category presents charges andutilization for angiography, cardiac catheterization, myocardialimaging, myelography, and other related invasive testing. Forutilization, the numerator unit is services or tests. The thirdsub-service category is functional testing. This sub-service categorypresents charges and utilization for electrocardiograms, cardiovascularstress tests, echography, and other related functional testing. Forutilization, the numerator unit is services or tests.

The laboratory and pathology (lab/path) service category presentscharges and utilization for laboratory and pathology services incurredin the physician's office, clinic, outpatient department of a hospital,or surgicenter. For utilization, the numerator unit is services. Thereare two sub-service categories. The first sub-service category islaboratory (lab). This sub-service category presents charges andutilization for laboratory services incurred in the physician's office,clinic, outpatient department of a hospital, or surgicenter. Forutilization, the numerator unit is services. The second sub-servicecategory is pathology (path). This sub-service category presents chargesand utilization for pathology services incurred in the physician'soffice, clinic, outpatient department of a hospital, or surgicenter. Forutilization, the numerator unit is services.

The medical and surgical procedures (med/surg) service category presentscharges and utilization for medical and surgical procedures incurred inthe physician office, clinic, outpatient department of a hospital, andsurgicenter. For utilization, the numerator unit is services orprocedures. There are two sub-service categories. The first sub-servicecategory is medical (med). This sub-service category presents chargesand utilization for ophthalmological services (including eye exams),electro-oculography, otolaryngologic exam, evaluation of speech/voice,cardiac rehabilitation, muscle testing, neurobehavioral exams, andrelated medical procedures. For utilization, the numerator unit isservices or procedures. The second sub-service category is surgical(surg). This sub-service category presents charges and utilization forsurgical procedures incurred in the physician office, clinic, outpatientdepartment of a hospital, or surgicenter. For utilization, the numeratorunit is services or procedures.

The prescription drugs (Rx) service category presents charges andutilization for outpatient and ambulatory prescription drugs. Forutilization, the numerator unit is prescription drug fills. Thesub-service category also is prescription drugs. This sub-servicecategory presents charges and utilization for outpatient and ambulatoryprescription drugs.

The professional inpatient services (prof inpt) service categorypresents charges and utilization for all inpatient professionalservices. For utilization, the numerator unit is services. Thesub-service category also is inpatient professional.

The facility outpatient visits (outpt facility) service categorypresents charges and utilization for services incurred in an outpatientdepartment of a hospital or surgicenter. For utilization, the numeratorunit is visits. There are two sub-service categories. The firstsub-service category is emergency room facility. This sub-servicecategory presents charges and utilization for emergency room facilityservices. For utilization, the numerator unit is visits. The secondsub-service category is other outpatient facility. This sub-servicecategory presents charges and utilization for other outpatient facilityservices, including medical/surgical, rehabilitation, and other servicesincurred in an outpatient department of a hospital or surgicenter. Forutilization, the numerator unit is visits.

The facility inpatient days (hosp inpt days) service category presentscharges and utilization for inpatient days for all hospital inpatientfacility services. For utilization, the numerator unit is hospitalinpatient days. The sub-service category also is inpatient facilitydays.

The facility inpatient admissions (hosp inpt admits) service categorypresents utilization for admissions for all hospital inpatient facilityservices. For utilization, the numerator unit is admissions. Charges arenot presented for this service category. For charges, this servicecategory is entered as “0,” because the episode charge component isassigned to the Facility Inpatient Days service category. Thesub-service category also is inpatient facility admissions.

The alternative sites (altern sites) service category presents chargesand utilization for skilled nursing facility and half-way home services.For utilization, the numerator unit is services. The sub-servicecategory also is alternative sites.

The other medical services (other med) service category presents chargesand utilization for other professional medical services incurred in thephysician's office, clinic, outpatient department of a hospital, anddialysis center. Other medical services include physical therapy,chiropractic services (other than professional visits), chemotherapy andradiation, dental, durable medical equipment, and ambulance services.For utilization, the numerator unit is services. There are sixsub-service categories. The first sub-service category is physicaltherapy. This sub-service category presents charges and utilization formanual therapy, electric simulation and other modalities, orthoticstraining, prosthetic training, and related physical therapy services.For utilization, the numerator unit is services.

The second sub-service category is dialysis. This sub-service categorypresents charges and utilization for end-stage renal disease (ESRD),hemodialysis, hemoperfusion, and related dialysis services. Forutilization, the numerator unit is services. The third sub-servicecategory is chemo/radiology. This sub-service category presents chargesand utilization for chemotherapy administration, provision ofchemotherapy agents, radiation dosimetry, brachytherapy isodose plans,radiation treatment delivery, and other related chemo/radiationservices. For utilization, the numerator unit is services. The fourthsub-service category is anesthesia. This sub-service category presentscharges and utilization for anesthesia. For utilization, the numeratorunit is services. The fifth sub-service category is durable medicalequipment (DME). This sub-service category presents charges andutilization for crutches, walkers, commode chairs, pressure pads, beds,portable oxygen, breast pumps, infusion supplies, wheelchairs, andrelated DME services. For utilization, the numerator unit is services.The sixth sub-service category is other medical care. This sub-servicecategory presents charges and utilization for other medical care noteasily classified elsewhere (e.g., ambulance, influenza immunization,dental not classified elsewhere). For utilization, the numerator unit isservices.

Step 1. Build Flattened CLI Structure Input File

The traditional structure of CLI input files is hierarchical. In ahierarchical structure, there is a family (or subscriber) unit, and theindividual members within the family are associated with the familyunit. Then, the claim submissions for a member are associated to themember. This claim record generally contains information such asprovider ID, provider specialty type, name of provider, and place ofservice. Finally, the CLIs within a claim are associated with theparticular claim. The CLIs generally contain the detailed recordinformation of each individual service rendered by the healthcareprovider (e.g., CPT-4 code, ICD.9 (diagnosis) codes, number of servicesprovided, service start and end dates).

Therefore, in a hierarchical structure, there are at least fourdifferent record types: family, member, claim, and CLI.

An advantage of the hierarchical structure is that it gives the user onedata file, which generally is easy to manage. Furthermore, thisstructure is intuitive, as the structure is generally how claimsprocessors at health plans think about organizing the submitted claimsdata.

The disadvantage of the hierarchical structure is that reading therecords from the claim input file into the software takes significantlymore CPU requirements as compared to the flattened CLI structureemployed in embodiments of the present invention. Therefore, thehierarchical structure requires significantly higher software systemprocessing time.

For the flattened CLI structure, there is only one record type producedfor each CLI. Moreover, all records in the file are the exact same typeand format. Therefore, each record forms a block that consists of agiven number of the exact same bytes.

The flattened CLI structure contains all record field information thatis present in the hierarchical CLI structure. Therefore, CLI recordsfrom members in the same family need to contain repeating family,member, and some unique claim information. On the surface, one may thinkthat the repetition of family, member, and claim field variables on eachCLI record will form a larger data file as compared to the hierarchicalCLI structure.

However, this is not the case because the hierarchical CLI structurerequires a ‘marker’ after each record to signify the start of anotherrecord. For example, in an embodiment, a marker is needed to signifythat the family record information has ended and the member informationbegins; a marker is needed to signify that the member information hasended and the claim information begins; and a marker is needed tosignify that the claim information has ended and the first CLIinformation for the claim begins.

Another issue with the hierarchical CLI structure is that the number ofsubordinate blocks of data is variable and, therefore, separate markersmust be used to encode this information. For example, a family may havefrom one to N number of family members. Likewise, a single member mayhave from one to N number of claims, and a claim may have from one to Nnumber of CLIs. In each of these cases, some type of encoding markermust be used to include this information into the data file. AdditionalCPU time is used in the software to read and handle these additionalmarkers.

The volume of required markers within the hierarchical CLI structuremakes the data file size similar to that of the flattened CLI structure.

The advantage of the flattened CLI structure is that the data file iseasily read into a medical claims-based software, requiringsignificantly less CPU requirements as compared to a hierarchical CLIstructure. The reason for less CPU intensive record reading is thatcomputers like to read fixed length records of the same type and format(i.e., blocks of data). The overall read step processing time, then, issignificantly reduced.

Step 2: Read in Run.INI File

The operation of the system of the present invention is influenced byparameters. Parameters are named controls found within the system of thepresent invention run initialization file (or RUN.INI File). Controlsinfluence the results generated by the system of the present invention.Table 6 presents the parameters in the RUN.INI file.

TABLE 6 Parameters in the RUN.INI File Parameter Name Notes ValuesModule Control Programs RUN_PATAN Controls whether the PATAN module is 0= No executed during the current run. 1 = Yes Initial System setting = 1RUN_PROVSPEC Controls where the PROVSPEC module is 0 = No executedduring the current run. 1 = Yes Initial System setting = 1 RUN_PROVANControls whether the PROVAN module is 0 = No executed during the currentrun. 1 = Yes Initial System setting = 1 General Directory ParametersDIR_BIN Defines the location of program files. Directory pathDIR_SYSTABLE Defines the location of system methodology Directory pathtables (see the “Control Tables” section of this manual). DIR_DATADefines the root directory for all data files, Directory path both inputand output. DIR_RUNTABLE Defines the location of both data-specificDirectory path tables and pre-specified tables (see the “Control Tables”section of this manual). FILE_PROVIDER Defines the location of thephysician File Name specialty file (see the “Data-Specific Tables”section of this manual). FILE_GROUPCODEMAP Defines the detail groupingcode to the File Name aggregate grouping code. Module Runtime ParametersGrouper function SWITCH AGGREGATESTART Defines the start number for theAggregate 0 = Do not eliminate any Grouping Codes to be processed. Formore Aggregate Grouping information on Aggregate Grouping Codes Codesfrom the beginning see the chapter, “Report Group Structures”. of thelist NOTE: Leave the value of this switch at 0 unless you want to limitthe groups to be N (any whole number) = processed. Specifies the firstAggregate Grouping Code to be processed. All codes that are smaller thanthis value will not be processed Initial System setting = 0SWITCH_AGGREGATEEND Defines the end number of the Aggregate 0 = Do noteliminate any Grouping Codes to be processed. For more AggregateGrouping information on Aggregate Grouping Codes Codes from the end ofthe see the chapter, “Report Group Structures.” list N (any wholenumber) = Specifies the last Aggregate Grouping Code to be processed.All codes that are larger than this value will not be processed. InitialSystem setting = 0 FILE_SPECAGE Identifies the file containing the agecontrol File Name with respect to table for each specialty. DIR_RUNTABLEInitial System setting = specage.tab FILE_MBCONDITIONS Identifies thefile that relates medical File Names with respect to conditions toclassifications in accordance DIR_RUNTABLE with the present inventions.Initial System setting = mbconditions.tab PATAN SWITCH_DROPPARTIALControls whether partial episodes are 0 = Include included in analysis.1 = Exclude Initial System setting = 1 SWITCH_DROPCOMORB Controlswhether comorbid episodes are 0 = Include included in analysis. 1 =Exclude Initial System setting = 1 SWITCH_ASSIGNTHRESHOLD Defines apercent whereby when a physician Any whole number has this percent ormore of total professional representing a percent charges associatedwith an episode, that Initial System setting = 20 episode is assigned tothe physician. The professional charges considered for this thresholdmay occur in an office visit, clinic, hospital outpatient, hospitalinpatient, or other professional setting (e.g., nursing home, halfwayhome, home visit professional charges). All facility charges andprescription drug charges are excluded. PROVSPEC NONE PROVANSWITCH_LOWOUTPERCENT Defines what percentage of a physician's 0 = 0.0%least expensive episodes will be removed 1 = 1.0% from analysis. PROVANremoves episodes 2 = 2.5% from each medical condition in the 3 = 5.0%physician's marketbasket separately. 4 = 10.0% PROVAN starts with theleast expensive Initial System setting = 2 episode and continuesremoving episodes in order of expense until the specified percentage ofepisodes is reached. SWITCH_LOWOUTDOLLAR Sets a threshold for episodecharges. All A whole number episodes below the value of this switch willrepresenting a dollar value. be dropped from analysis. Initial Systemsetting = 20 SWITCH HIGHOUTPERCENT Defines what percentage of aphysician's 0 = 0.0% most expensive episodes will be removed 1 = 1.0%from analysis. PROVAN removes episodes 2 = 2.5% from each medicalcondition in the 3 = 5.0% physician's marketbasket. PROVAN starts 4 =10.0% with the most expensive episode and Initial System setting = 3continues removing episodes in order of expense until the specifiedpercentage of episodes is reached. SWITCH_HIGHOUTDIFF The parameterSWITCH_HIGHOUTDIFF A whole number that determines whether a signalepisode should represents a percent. be removed as a high-outlier. Thishigh-end NOTE: Should always outlier parameter is applied when one high-be ≧100. If ≦100, end outlier cannot be removed under the then anepisode will SWITCH_HIGHOUTPERCENT parameter. ALWAYS be removed. Thevalue of this parameter is a whole Initial System setting = 250 numberrepresenting a percent. If the charges for the most expensive episodeare at least the defined percent greater than the charges for the nextmost expensive episode, the most expensive episode is removed as a highoutlier. A maximum of one episode for each medical condition in eachphysician's marketbasket may be removed using this rule.SWITCH_MINEPCOUNT Sets the requirement for the number of Any wholenumber episodes a physician must treat to be Initial System setting = 2included in the analysis. This parameter implement part of the N × 3rule, which specifies that a physician must treat N episodes in threemedical conditions to be included. For example, if the N value is equalto four, the rule would require four episodes in each of threeconditions, and the rule would become, in effect a “4 × 3” rule. In theN × 3 rule: N = The number of episodes of a specific medical condition aphysician must treat during the study period. This number can be changedby the user. 3 = the minimum number of medical conditions in which thephysician must treat episodes. The medical conditions must be in thephysician's marketbasket . This number cannot be changed. SWITCHCONFLEVEL Sets the p value for statistical confidence. 1 = 0.75 (p <0.25) 2 = 0.90 (p < 0.10) Initial System setting = 1 PATAN DateParameters STUDYSTARTDATE Defines the start date of the study period. Adate in the format yyyymmdd STUDYENDDATE Defines the end date of thestudy period. A date in the format yyyymmdd STUDYMIDDATE Sets themidpoint date of the study period. A A date in the format chronicepisode of care must start on or yyyymmdd before this date. STUDYQ4DATEDefines the date that is the end of the third A date in the formatquarter of the study period (the last day yyyymmdd before the fourthquarter starts). An acute episode of care from a medical condition witha window period 120 days must start on or before this date. SliderParameters STUDYSLIDER1_START Sets the start date of the slider periodfor A date in the format Slider 1. yyyymmdd STUDYSLIDER1_END Sets theend date of the slider period for A date in the format Slider 1.yyyymmdd STUDYSLIDER2_START Sets the start date of the slider period forA date in the format Slider 2. yyyymmdd STUDYSLIDER2_END Sets the enddate of the slider period for A date in the format Slider 2. yyyymmddDIR_PATSORT Identifies the subdirectory that receives the Directory namePATSORT output. This subdirectory is within Initial System setting = theDIR DATA directory path. patsort DIR_PATAN Identifies the subdirectorythat receives the Directory name PATAN output. This subdirectory iswithin Initial System setting = the DIR_DATA directory path. patanDIR_PROVSORT1 Identifies the subdirectory that receives the Directoryname PROVSORT1 output. This subdirectory is Initial System setting =within the DIR_DATA directory path. provsort1 DIR_PROVSPEC Identifiesthe subdirectory that receives the Directory names PROVSPEC output. Thissubdirectory is Initial System setting = within the DIR_DATA directorypath. provspec DIR_PROVSORT2 Identifies the subdirectory that receivesthe Directory name PROVSORT2 output. This subdirectory is Initial Systemsetting = within the DIR_DATA directory path. provsort2 DIR_PROVANIdentifies the subdirectory that receives the Directory name PROVANoutput. This subdirectory is within Initial System setting = theDIR_DATA directory path. provan Data file Parameters - within DIR_DATACOREFILE Defines the subdirectory and filename that Directory name/Filename contains the input claims file. The Initial System setting =subdirectory is within the DIR_DATA extract/corefields directory path.CORESORTED Defines the subdirectory and filename that Directoryname/File name contains the sorted claims file. The Initial Systemsetting = subdirectory is within the DIR_DATA patsort/sampledata. sortdirectory path. ASNFILE Defines the subdirectory and filename thatDirectory name/File name contains the output file from PATAN. TheInitial System setting = subdirectory is within the DIR_DATApatan/assign.tab directory path. ASNSORTED Defines the subdirectory andfilename that Directory name/File name contains the sorted output filefrom PATAN. Initial System setting = The subdirectory is within theDIR_DATA provsort1/assign.tab.sort directory path. ASNSPECFILE Definesthe subdirectory and filename that Directory name/File name contains theoutput file from PROVSPEC. Initial System setting = The subdirectory iswithin the DIR_DATA provspec/assignspec.tab directory path.ASNSPECSORTED Defines the subdirectory and filename that Directoryname/File name contains the sorted output file from Initial Systemsetting = PROVSPEC. The subdirectory is within theprovsort2/assignspec.tab.sort DIR_DATA directory path. SCOREFILE Definesthe subdirectory and filename that Directory name/File name contains oneof the two final output files. The Initial System setting = subdirectoryis within the DIR_DATA provan/score.tab directory path. DETAILFILEDefines the subdirectory and filename that Directory name/File namecontains one of the two final output files. The Initial System setting =subdirectory is within the DIR_DATA provan/detail.tab directory path.Step 3: Read in CLIs from Flattened CLI Structure

The CLIs in the Flattened CLI Structure are now read into the patientsort (PATSORT). PATSORT sorts CLIs by the primary sort key of member (orpatient) and the secondary sort key of date of service on each CLI.During PATSORT, all CLIs with zero dollars in charges ($0) are removedfrom further analysis.

Step 4: Apply Sliders

An embodiment of the present invention uses sliders to establish that amember was present during an ongoing condition-specific episode of care.The purpose of sliders is to establish the presence of members duringongoing condition-specific episodes of care without using an eligibilityfile. Often, membership eligibility files are not readily accessible tothe user.

An embodiment of the present invention employs two sliders, each ofwhich can be set with a start date and an end date. These dates can beset by the user. The period that includes the start and end dates andthe time in between is the slider period. The use of sliders allows theuser to establish that a member was present at least for some period oftime near the beginning and near the end of the study period. If so,then the user concludes that the member was present during the ongoingcondition-specific episode of care.

An embodiment of the present invention checks to see that the member wasrepresented by a CLI that began and ended during each slider period. Ifnot, then the member and all CLIs related to that member are removedfrom the analysis.

The two sliders are referred to herein as Slider 1 and Slider 2. Sliderperiod settings for a calendar year study period are as follows: Slider1 is set for the time period of January 1 through June 30. (If not usinga calendar year, then use the first six months of the study period.)Slider 2 is set for the time period of July 1 through December 31. (Ifnot using a calendar year, then use the second six months of the studyperiod.) With these settings, a member must have a claim in both thefirst and second halves of the year to be included in the analysis.

Table 7 illustrates examples of suggested slider settings for a studyperiod that starts on January 1 and ends on December 31.

TABLE 7 Recommended Slider Settings Example # Slider Settings Notes 1Slider period 1: January With these settings, a member must 1 throughJune 30 have one final adjudicated claim in Slider period 2: July 1 eachslider period to be included in through December 31 the analysis. Thesesettings increase the likelihood that a member included in the analysiswas in fact present during an ongoing episode of care. 2 Slider period1: March 1 A member who has one final through December 31 adjudicatedclaim during slider period Slider period 2: March 1 1 is assumed to bepresent during the through December 31 entire year. Slider 2 is ignoredbecause its slider period is identical to Slider 1's period. Thissetting keeps many members in the analysis.Step 5: Perform PATAN Analysis to Form Episodes of Care

The Patient Analysis (PATAN) forms episodes of care using a Grouperfunction explained herein. The Grouper function is based on theInternational Classification of Diseases, 9^(th) revision (ICD.9) andthe Current Procedural Terminology, 4^(th) edition (CPT-4). The Grouperfunction groups together over 14,000 unique ICD.9 diagnosis codes into526 meaningful medical conditions. Each ICD.9 code is assigned to asingle medical condition.

The resulting 526 medical conditions are formed based on clinicalhomogeneity with respect to generating a similar clinical response fromphysicians treating a patient. Table M shows selected ICD.9 codes mappedto several medical conditions.

TABLE M Selected Diagnosis (ICD.9) Codes Mapped to Medical ConditionsMedical Condition Medical Condition ICD.9 Number Long Description CodesBrief Description 5.2 Conjunctivitis 077.0 Conjunctivitis, inclusion077.8 Conjunctivitis, viral 372.0 Conjunctivitis, acute 372.01Conjunctivitis, serous 372.1 Conjunctivitis, chronic 372.14Conjunctivitis chronic allergic 372.22 Contact blepharonconjunctivitist6.5 Otitis media 381 Eustachian tube disorder 381.02 Acute mucoid otitismedia 381.06 Acute allergic sanguinous otitis media 381.20 Chronicmucoid otitis media 382 Suppurative otitis media 382.00 Acutesuppurative otitis media 382.4 Suppurative otitis media 382.01 Acutesuppurative, with drum rupture 382.1 Chronic tubotympanic suppurative7.2 Sinusitis 461.0 Acute maxillary sinusitis 461.2 Acute ethomoidalsinusitis 461.3 Acute sphenoidal sinusitis 473 Chronic sinusitis 473.2Chronic ethmoidal sinusitis 473.3 Chronic sphenoidal sinusitis 9.11Asthma 493.0 Extrinsic asthma 493.02 Extrinsic asthma, acuteexacerbation 493.1 Intrinsic asthma 493.01 Extrinsic asthma, statusasthmaticus 493.2 Chronic obstructive asthma 493.21 Chronic obstructive,status asthmaticus 10.2 Hypertension 401.1 Benign essential hypertension405.1 Secondary benign hypertension 402 Hypertensive heart disease 402.0Hypertensive heart disease, malignant 403.00 Hypertension renal,malignant 403.1 Hypertension renal, benign disease 405.0 Secondarymalignant hypertension 402.11 Hypertensive heart, malignant, heartfailure 404.01 Hypertensive heart/renal, malignant health failure 404.11Hypertensive heart/renal, benign, heart failure

The 526 medical conditions are placed into one of 37 Principle MedicalCondition Groups (PMC Groups). The PMC Groups generally represent organ,body, or medical condition types (e.g., PMC Group 5-Eye Conditions; PMCGroup 9-Respiratory Conditions; PMC Group 24-Mental Disorders). Table 8presents the list of PMC Groups.

TABLE 8 Principle Medical Condition (PMC) Groups Principle MedicalCondition PMC Group PMC Group Groups Long Description AbbreviatedDescription 1 Preventive Care Preventive Care 2 Infectious and ParasiticInfectious & Parasitic Dz Diseases 3 Human Immunodeficiency HIVInfections Infections 4 Nervous System Conditions Nervous SystemConditions 5 Eye Conditions Eye Conditions 6 Ear Conditions EarConditions 7 Nose Conditions Nose Conditions 8 Mouth Conditions MountConditions 9 Respiratory Conditions Respiratory Conditions 10 Heart andPulmonary Heart and Pulmonary Cond Conditions 11 Cerebrovascular andArtery Cerebrovasc & Artery Cond Conditions 12 Vein and Lymphatic Vein &Lymphatic Cond Conditions 13 Digestive System Conditions DigestiveSystem Cond 14 Hernias Hernias 15 Hepatobiliary System and HepatobiliarySys & Pancreas Pancreas 16 Thyroid Disorders Thyroid Disorders 17Diabetes Mellitus Diabetes Mellitus 18 Other Endocrine Disorders OtherEndocrine Disorders 19 Metabolic Disorders Metabolic Disorders 20Immunity and Blood Disorders Immunity & Blood Disorders 21 Lymphatic andHematopoietic Lymph & Hematopoietic Tiss Tissue 22 Urinary Tract andKidney Urinary Tract & Kidney Cond Conditions 23 Female ReproductiveFemale Reproductive Cond Conditions 24 Male Reproductive Conditions MaleReproductive Cond 25 Infertility Treatment Infertility Treatment 26Maternity-Related Conditions Maternity-Related Cond 27 NeonatalConditions Neonatal Conditions 28 Congenital Anomalies CongenitalAnomalies 29 Skin and Subcutaneous Tissue Skin & Subcutaneous TissueConditions 30 Breast Conditions Breast Conditions 31 MusculoskeletalConditions Musculoskeletal Conditions 32 Upper Limb Conditions UpperLimb Conditions 33 Lower Limb Conditions Lower Limb Conditions 34 MentalDisorders Mental Disorders 35 Burns Burns 36 Other Medical ConditionsOther Medical Conditions 37 Replaced Diagnosis Codes Replaced DiagnosisCodes

Within each PMC Group, medical conditions are listed in ascending orderof expected resource intensity level and physiologic progression of thecondition or disease (from least resource intensive and physiologicprogression to the most resource intensive and physiologic progression).Table 9 shows an example for PMC Group 6, Ear Conditions.

TABLE 9 PMC Group 6-Ear Conditions Medical Condition Medical ConditionNumber Long Description 6 Ear Conditions 6.1 Otitis externa 6.2 Wax inear 6.3 Open wound of ear 6.4 Other disorders of ear 6.5 Otitis media6.6 Disorders of tympanic membrane 6.7 Disorders of middle ear 6.8Vertiginous syndromes 6.9 Mastoiditis 6.10 Hearing loss 6.11 Malignantneoplasm of middle ear

The 526 medical conditions in the Grouper function account for 100% ofall medical conditions and expenditures as identified by ICD.9 medicalcondition diagnostic codes. Each condition receives a Medical ConditionNumber (e.g., Medical Condition 4.1-neuritis upper and lower limbs;Medical Condition 5.16-glaucoma; Medical Condition 7.2-sinusitis;Medical Condition 9.11-asthma; Medical Condition 10.13-ischemic heartdisease). Table 10 presents the list of medical conditions in theGrouper function.

TABLE 10 List of Medical Conditions in Grouper Function Number Medicalof Condition Medical Condition Medical Condition Severity Number LongDescription Abbrev Description Classes 1 Preventive Care Preventive Care— 1.1 General medical exam General medical exam 1 1.2 Gynecological examGynecological exam 1 1.3 Screenings for medical conditions Screening ofmed conditions 1 1.4 Vaccinations Vaccinations 1 1.5 Prophylactictherapy Prophylactic therapy 1 1.6 History of medical conditions Hx ofmedical conditions 1 1.7 Postpartum exam Postpartum exam 1 1.8 Surgicalaftercare Surgical aftercare 1 2 Infectious and Parasitic DiseasesInfectious & Parasitic Dz — 2.1 Intestinal infections Intestinalinfections 1 2.2 Other bacteria disease Other bacteria diseases 3 2.3Drug-resistant microorganism Drug-resistant microorganism 1 2.4Septicemia Septicemia 2 2.5 Tuberculosis Tuberculosis 3 2.6 Other viraldiseases Other viral diseases 3 2.7 Chickenpox Chickenpox 3 2.8 Herpessimplex Herpes simplex 3 2.9 Viral warts Viral warts 1 2.10 Infectiousmononucleosis Infectious mononucleosis 1 2.11 Cytomegalic inclusiondisease Cytomegalic inclusion dz 1 2.12 Non-arthropod-borne viraldiseases Non-arth-borne viral dz 3 2.13 Arthropod-borne diseasesArthropod-borne dz 3 2.14 Venereal diseases Venereal diseases 3 2.15Other mycoses Other mycoses 1 2.16 Cryptococcosis Cryptococcosis 1 2.17Candidiasis Candidiasis 3 2.18 Coccidioidomycosis Coccidioidomycosis 32.19 Histoplasmosis Histoplasmosis 3 2.20 Blastomycotic infectionBlastomycotic infection 2 2.21 Helm inthiases Helm inthiases 3 2.22Scabies Scabies 1 2.23 Toxoplasmosis Toxoplasmosis 3 2.24 PneumocystosisPneumocystosis 1 2.25 Other infectious diseases Other infectiousdiseases 3 3 Human Immunodeficiency Infections HIV Infections — 3.1 HIVinfection with no complications HIV n/no complications 1 3.2 HIVinfection with infectious complication HIV with infectious comp 3 3.3HIV infection with CNS involvement HIV with CNS involvement 3 3.4 HIVinfection with malignancy HIV with malignancy 3 3.5 HIV infection withmultiple complications HIV with multiple comp 3 4 Nervous SystemConditions Nervous System Conditions — 4.1 Neuritis upper and lowerlimbs Neuritis upper, lower limbs 2 4.2 Peripheral neuropathy Peripheralneuropathy 3 4.3 Headaches Headaches 2 4.4 Disorders of cranial nervesDisorders of cranial nerves 2 4.5 Carpal tunnel syndrome Carpal tunnelsyndrome 1 4.6 Benign neoplasm of non-CNS nerves Benign neop non-CNSnerves 1 4.7 Nerve root and plexus disorder Nerve root and plexus dsdr 34.8 Tremor disorders Tremor disorders 2 4.9 Injury to peripheral nervesand nerve roots lnj peripheral nerv & nerv roots 3 4.10Neurofibromatosis Neurofibromatosis 1 4.11 Inflammatory diseases of CNSInflammatory dz of CNS 1 4.12 Paralytic syndromes Paralytic syndromes 34.13 Myoneural disorders Myoneural disordes 2 4.14 Benign neoplasm ofCNS Benign neoplasm of CNS 1 4.15 Injury of spinal cord Injury of spinalcord 3 4.16 Congenital anomalies of nervous system Cong anomalies nervsys 3 4.17 Parkinson's disease Parkinson's disease 1 4.18 Seizuredisorders Seizure disorders 3 4.19 Multiple sclerosis Multiple sclerosis1 4.20 Other CNS diseases Other CNS diseases 3 4.21 Muscular dystrophiesMuscular dystrophies 2 4.22 Malignant neoplasm of non-CNS nerves Maligneop non-CNS nerves 1 4.23 Malignant neoplasm of spinal cord Malig neopspinal cord 1 4.24 Malignant neoplasm of brain, initial care Malig neopbrain, initial 1 4.25 Malignant neoplasm of brain, active care Maligneop brain, active 1 4.26 Malignant neoplasm of brain, inactive careMalig neop brian, inactive 1 5 Eye Conditions Eye Conditions — 5.1Refractive errors Refractive errors 1 5.2 Conjunctivits Conjunctivitis 25.3 Other disorders of conjunctiva Other dsdr of conjunctiva 2 5.4Infections of the eyelids Infections of the eyelids 2 5.5 Disorders ofeyelids Disorders of eyelids 2 5.6 Disorders of lacrimal system Dsdr oflacrimal system 2 5.7 Keratitis Keratitis 3 5.8 Other disorders ofcornea Other disorders of cornea 3 5.9 Disorders of iris and ciliarybody Dsdr iris and ciliary body 3 5.10 Strabismus Strabismus 3 5.11External eye injury External eye injury 2 5.12 Disorders of globeDisorders of globe 3 5.13 Internal eye injury Internal eye injury 2 5.14Disorders of vitreous body Disorders of vitreous body 2 5.15 Other eyedisorders Other eye disorders 3 5.16 Glaucoma Glaucoma 3 5.17 CataractCataract 3 5.18 Other retinal disorders Other retinal disorders 3 5.19Macular degeneration Macular degeneration 2 5.20 Retinal detachments anddefects Retinal detach & defects 3 5.21 Blindness and visualdisturbances Blindness & visual disturb 3 5.22 Malignant neoplasm of eyeMalignant neoplasm of eye 1 6 Ear conditions Ear Conditions — 6.1 Otitisexterna Otitis externa 3 6.2 Wax in ear Wax in ear 1 6.3 Open wound ofear Open wound of ear 3 6.4 Other disorders of ear Other disorders ofear 3 6.5 Otitis media Otitis media 3 6.6 Disorders of tympanic membraneDsdr of tympanic membrane 3 6.7 Disorders of middle ear Disorders ofmiddle ear 3 6.8 Vertiginous syndromes Vertiginous syndromes 3 6.9Mastoiditis Mastoiditis 3 6.10 Hearing loss Hearing loss 3 6.11Malignant neoplasm of middle ear Malig neop of middle ear 1 7 NoseConditions Nose conditions — 7.1 Rhinitis Rhinitis 2 7.2 SinusitisSinusitis 2 7.3 Other nasal disorders Other nasal disorders 3 7.4Deviated nasal septum Deviated nasal septum 1 7.5 Nasal bone fractureNasal bone fracture 2 7.6 Malignant neoplasm of nasal cavities Maligneop of nasal cavities 3 8 Mouth Conditions Mouth Conditions — 8.1 Cleftpalate and lip Cleft palate and lip 3 8.2 Congenital anomalies of oralcavity Cong anomalies oral cavity 2 8.3 Congenital anomalies of face,jaw, skull Cong anom face, jaw, skull 2 8.4 Disorders of teeth Disordersof teeth 3 8.5 Open wound of face and mount Open wound face & mouth 38.6 Anomalies of jaw size Anomalies of jaw size 1 8.7 Other dentofacialanomalies Other dentofacial anom 1 8.8 Gingival and periodontal diseasesGingival & periodontal dz 2 8.9 Other disease of supporting structureOther dz supporting struct 1 8.10 Temporomandibular joint disorder TMJdisorder 1 8.11 Other dentofacial disorders Other dentofacial disorders3 8.12 Diseases of jaws Diseases of jaws 2 8.13 Disease of salivaryglands Diseases of salivary glands 3 8.14 Diseases of oral soft tissueDiseases of oral soft tissue 3 8.15 Benign neoplasm of oral cavityBenign neop of oral cavity 2 8.16 Jaw fracture Jaw fracture 3 8.17Malignant neoplasm of oral cavity Malig neop oral cavity 3 9 RespiratoryConditions Respiratory Conditions — 9.1 Upper respiratory infectionsUpper respiratory infections 3 9.2 Diseases of upper respiratory tractDz upper respiratory tract 3 9.3 Lower respiratory diseases Lowerrespiratory disease 3 9.4 Acute bronchitis Acute bronchitis 2 9.5Hypertrophy of tonsils and adenoids Hypertrophy tonsils & aden 2 9.6Congenital anomaly of respiratory system Cong anon respire system 3 9.7Pneumonia Pneumonia 3 9.8 Disorders of lower respiratory tract Dsdr oflower respir tract 1 9.9 Pleurisy Pleurisy 2 9.10 Chronic bronchitisChronic bronchitis 2 9.11 Asthma Asthma 3 9.12 Benign neoplasm ofbronchus and lung Benign neop bronchus & lung 3 9.13 Emphysema Emphysema2 9.14 Chronic obstructive pulmonary disease COPD 1 9.15 Spontaneouspneumothorax Spon pneumothorax 1 9.16 Lung transplant Lung transplant 19.17 Malignant neoplasm of pharynx and larynx Malig neop pharyn & laryn2 9.18 Malignant neoplasm of pleura Malig neop of pleura 2 9.19Malignant neoplasm of bronchus and lung, Malig neop bron/lung, active 2active 9.20 Malignant neoplasm of bronchus and lung, Malig neopbron/ling, inactive 2 inactive 10 Heart and Pulmonary Conditions Heartand Pulmonary Cond — 10.1 Abnormal heart beat Abnormal heart beat 2 10.2Hypertension Hypertension 3 10.3 Congenital anomaly of circulatorysystem Cong anom circulatory sys 3 10.4 Ventricular arrhythmiasVentricular arrhythmias 3 10.5 Supraventricular arrhythmiasSupraventricular arrhythmias 3 10.6 Atrial septal defect Atrial septaldefect 2 10.7 Ventricular septal defect Ventricular septal defect 2 10.8Angina pectoris Angina pectoris 1 10.9 Rheumatic fever Rheumatic fever 210.10 Conduction disorders Conduction disorders 3 10.11 Other heartdisease Other heart disease 3 10.12 Rheumatic heart disease Rheumaticheart disease 2 10.13 Ischemic heart disease Ischemic heart disease 310.14 Heart value disorders Heart value disorders 3 10.15 Pulmonaryheart disease Pulmonary heart disease 3 10.16 Congestive heart failureCongestive heart failure 2 10.17 Cardiomyopathy Cardiomyopathy 2 10.18Other aneurysm Other aneurysm 3 10.19 Aortic aneurysm, initial Aorticaneurysm, initial 2 10.20 Aortic aneurysm, follow-up Aortic aneurysm,follow-up 2 10.21 Acute myocardial infarction, active Acute myocardialinfrct, active 2 10.22 Acute myocardial infarction, follow-up Acutemyocardial infct, fup 2 10.23 Heart transplant Heart transplant 1 10.24Malignant neoplasm of mediastinum Malig neop of mediastinum 2 10.25Malignant neoplasm of heart Malig neoplasm of heart 1 11 Cerebrovascularand Artery Conditions Cerebrovasc & Artery Cond — 11.1 Pigmented nevusPigmented nevus 1 11.2 Superficial injury of head and neck Superficialinjury head & neck 2 11.3 Contusion of head and neck Contusion of headand neck 1 11.4 Concussion Concussion 3 11.5 Cerebral lacerationCerebral laceration 3 11.6 Diseases of capillaries Diseases ofcapillaries 1 11.7 Disorders of arteries Disorders of arteries 3 11.8Generalized arteriosclerosis Generalized arteriosclerosis 3 11.9Fracture of skull Fracture of skull 3 11.10 Transient cerebral ischemiaTransient cerebral ischemia 3 11.11 Injury to blood vessels of head andneck Inj to bl vessels head & neck 1 11.12 Occlusion of cerebralarteries Occlusion of cerebral arteries 3 11.13 Cerebrovascularhemorrhage following injury Cerebro hemorrhage, injury 3 11.14Cerebrovascular hemorrhage Cerebrovascular hemorrhage 2 12 Vein andLymphatic Conditions Vein & Lymphatic Cond — 12.1 Anal fissure andfistula Anal fissure and fistula 2 12.2 Hemorrhoids Hemorrhoids 3 12.3Other peripheral vascular diseases Other peripheral vascular dz 3 12.4Varicose veins of other sites Varicose veins of other sites 3 12.5Varicose veins of lower extremities Varicose veins lower extreme 3 12.6Thrombophlebitis Thrombophlebitis 3 13 Digestive System ConditionsDigestive System Cond — 13.1 Helicobacter pylori infection Helicobacterpylori infection 1 13.2 Congenital anomaly of digestive system Cong anomdigestive system 1 13.3 Infectious diarrhea and gastroenteritis Infectdiarrhea/gastroenteritis 2 13.4 Other disorders of esophagus Otherdisorders of esophagus 3 13.5 Gastritis and duodenitis Gastritis andduodenitis 3 13.6 Gastroesophageal reflux Gastroesophageal relux 1 13.7Functional digestive disease Functional digestive disease 2 13.8Disorders of stomach and duodenum Dsdr stomach & duodenum 3 13.9Irritable colon Irritable colon 1 13.10 Peptic ulcer Peptic ulcer 313.11 Diverticula of intestine Diverticula of intestine 3 13.12 Otherdiseases of intestine Other diseases of intestine 3 13.13 Noninfectiousgastroenteritis and colitis Noninfect gastroent & colitis 3 13.14Appendicitis Appendicitis 3 13.15 Benign neoplasm of stomach Benignneoplasm of stomach 2 13.16 Benign neoplasm of small intestine Benignneoplasm small 2 intestine 13.17 Benign neoplasm of colon and rectumBenign neop colon/rectum 2 13.18 Intestinal obstruction Intestinalobstruction 2 13.19 Vascular insufficiency of intestine Vascularinsufficiency intest 2 13.20 Crohn's disease Crohn's disease 3 13.21Gastrointestinal hemorrhage Gastrointestinal hemorrhage 2 13.22Intestine and pancreas transplant Intest/pancreas transplant 1 13.23Malignant neoplasm of anus and rectum, initial Malig neop anus/rectum,initial 1 13.24 Malignant neoplasm of anus and rectum, Malig neopanus/rectum, active 1 active 13.25 Malignant neoplasm of anus andrectum, fup Malig neop anus/rectum, fup 1 13.26 Malignant neoplasm ofesophagus Malig neop of esophagus 3 13.27 Malignant neoplasm of stomachMalign neoplasm of stomach 1 13.28 Malignant neoplasm of small intestineMalig neop of small intestines 2 13.29 Malignant neoplasm of peritoneummalign neop of peritoneum 1 13.30 Malignant neoplasm of colon, initialMalig neop of colon, initial 2 13.31 Malignant neoplasm of colon, activeMalig neop of colon, active 2 13.32 Malignant neoplasm of colon, followup Malig neop of colon, fup 2 14 Hernias Hernias — 14.1 Other herniasite Other hernia site 3 14.2 Diaphragmatic hernia Diaphragmatic hernia3 14.3 External abdominal hernias External abdominal hernias 3 15Hepatobiliary System and Pancreas Hepatobiliary Sys & Pancreas — 15.1Congenital anomaly of hepatobiliary system Cong anom hepatobiliary sys 115.2 Other disorders of biliary tract Other disorders of biliary tract 315.3 Cholecystitis Cholecystitis 2 15.4 Cholelithiasis Cholelithiasis 315.5 Benign neoplasm of liver and biliary passages Benign neopliver/biliary pass 1 15.6 Other disorders of liver Other disorders ofliver 3 15.7 Hepatitis Hepatitis 3 15.8 Benign neoplasm of pancreasBenign neoplasm of pancreas 1 15.9 Diseases of pancreas Diseases ofpancreas 2 15.10 Chronic liver disease Chronic liver disease 3 15.11Liver transplant Liver transplant 1 15.12 Malignant neoplasm ofgallbladder Malign neop of gallbladder 2 15.13 Malignant neoplasm ofliver Malignant neoplasm of liver 2 15.14 Malignant neoplasm of pancreasMalig neop of pancreas 2 16 Thyroid Disorders Thyroid Disorders — 16.1Other disorders of thyroid Other disorders of thyroid 3 16.2 GoiterGoiter 1 16.3 Hypothyroidism Hypothyroidism 1 16.4 HyperthyroidismHyperthyroidism 3 16.5 Malignant neoplasm of thyroid Malignant neoplasmof thyroid 1 17 Diabetes Mellitus Diabetes Mellitus — 17.1 Diabetesmellitus with no complications Diabetes w/no complications 1 17.2Diabetes mellitus with ophthalmic Diabetes with ophthalmic 3manifestation 17.3 Diabetes mellitus with neurologic manifestationDiabetes with neurologic 3 17.4 Diabetes mellitus with circulatorymanifestation Diabetes with circulatory 3 17.5 Diabetes mellitus withrenal manifestation Diabetes with renal 3 17.6 Diabetes mellitus withmultiple complications Diabetes with multiple comp 3 18 Other EndocrineDisorders Other Endocrine Disorders — 18.1 Other endocrine disordersOther Endocrine Disorders 3 18.2 Disorders of adrenal gland Disorders ofadrenal gland 2 18.3 Disorders of pituitary gland Disorders of pituitarygland 3 18.4 Benign neoplasm of pituitary gland Benign neop of pituitarygland 1 18.5 Malignant neoplasm of other endocrine glands Malig neopother endo glands 2 18.6 Malignant neoplasm of thymus gland Malig neopof thymus gland 1 18.7 Malignant neoplasm of pituitary gland Malig neopof pituitary gland 1 18.8 Malignant neoplasm of adrenal gland Malig neopof adrenal gland 1 19 Metabolic Disorders Metabolic Disorders — 19.1III-defined metabolic symptoms III-defined metabolic symptoms 1 19.2Disorders of fluids and electrolytes Dsdr of fluids and electrolytes 319.3 Nutritional deficiencies Nutritional deficiencies 1 19.4 Disordersof lipid metabolism Disorders of lipid metabolism 2 19.5 Gout Gout 319.6 Other disorders of metabolism Other disorders of metabolism 3 19.7Cystic fibrosis Cystic fibrosis 2 20 Immunity and Blood DisordersImmunity & Blood disorders — 20.1 Congenital anomaly of spleenCongenital anomaly of spleen 1 20.2 Disease of blood forming organs Dzof blood forming organs 1 20.3 Disease of white blood cells Diseases ofwhite blood cells 1 20.4 Anemia disorders Anemia disorders 2 20.5Aplastic anemias Aplastic anemias 1 20.6 ThrombocytopeniaThrombocytopenia 1 20.7 Other disorders of blood Other disorders ofblood 1 20.8 Disorders of immune mechanism Dsdr of immune mechanism 320.9 Malignant neoplasm of spleen Malignant neoplasm of spleen 1 21Lymphatic and Hematopoietic Tissue Lymph & Hematopoietic Tiss — 21.1Lymphadenitis Lymphadenitis 1 21.2 Hemangioma Hemangioma 2 21.3 Othermalignant neoplasms of lymphoid tissue Other malig neop lymph tissue 321.4 Burkitt's tumor Burkitt's tumor 2 21.5 Lymphoma, active Lymphoma,active 2 21.6 Lymphoma, inactive Lymphoma, inactive 2 21.7 Hodgkin'sdisease, active Hodgkin's disease, active 2 21.8 Hodgkin's disease,inactive Hodgkin's disease, inactive 2 21.9 Sarcomas Sarcomas 2 21.10Leukemia, active Leukemia, active 2 21.11 Leukemia, inactive Leukemia,inactive 2 21.12 Multiple myeloma Multiple myeloma 2 22 Urinary Tractand Kidney Conditions Urinary Tract & Kidney Cond — 22.1 Other disordersof urethra Other disorders of urethra 2 22.2 Congenital anomalies ofbladder and urethra Cong anom bladder and urethra 2 22.3 Urinary tractinfections Urinary tract infections 2 22.4 Urethritis Urethritis 2 22.5Urethral stricture Urethral stricture 2 22.6 Other disorders of bladderOther disorders of bladder 3 22.7 Kidney infection Kidney infection 322.8 Hydronephrosis Hydronephrosis 1 22.9 Congenital anomalies of kidneyand ureter Cong anom kidney and ureter 3 22.10 Disorders of kidney andureter Disorders of kidney and ureter 3 22.11 Calculus of kidney andureter Calculus of kidney and ureter 2 22.12 GlomerulonephritisGlomerulonephritis 3 22.13 Bladder transplant Bladder transplant 1 22.14Renal dialysis Renal dialysis 1 22.15 Renal failure Renal failure 222.16 Kidney transplant, initial Kidney transplant, initial 1 22.17Kidney transplant, follow-up Kidney transplant, follow-up 1 22.18Malignant neoplasm of bladder and urethra Malig neop bladder and urethra1 22.19 Malignant neoplasm of kidney and ureter Malig neop kidney andureter 1 23 Female Reproductive Conditions Female Reproduction Cond —23.1 Disorders of cervix and vagina Disorders of cervix and vagina 323.2 Cervicitis and vaginitis Cervicitis and vaginitis 2 23.3Uterovaginal prolapse Uterovaginal prolapse 3 23.4 Other disorders ofuterus Other disorders of uterus 3 23.5 Other disorders of femalegenital organs Other dsdr female genital org 3 23.6 Ovarian dysfunctionOvarian dysfunction 3 23.7 Menstrual disorders Menstrual disorders 223.8 Menopausal symptoms Menstrual disorders 1 23.9 Benign neoplasm ofuterus Benign neoplasm of uterus 2 23.10 Endometriosis Endometriosis 223.11 Ovarian cyst Ovarian cyst 1 23.12 Carcinoma in situ of cervixCarcinoma in situ of cervix 1 23.13 Malignant neoplasm of placenta Maligneop of placenta 1 23.14 Malignant neoplasm of cervix and vagina Maligneop of cervix & vagina 2 23.15 Malignant neoplasm of ovary andfallopian Malig neop ovary & fallop tube 1 tube 23.16 Malignant neoplasmof uterus Malignant neoplasm of uterus 1 24 Male Reproductive ConditionsMale Reproductive Cond — 24.1 Hydrocele Hydrocele 2 24.2 Orchitis andepididymitis Orchitis and epididymitis 2 24.3 Disorders of male genitalorgans Dsdr of male genital organs 3 24.4 Disorders of penis Disordersof penis 2 24.5 Other disorders of prostate Other disorders of prostate3 24.6 Prostatic hypertrophy and prostatitis Prostatic hyertro &prostatitis 2 24.7 Malignant neoplasm of other male genital Malig neopother male gen org 3 organs 24.8 Malignant neoplasm of testis Malignantneoplasm of testis 1 24.9 Malignant neoplasm of prostate, active Maligneop of prostate, active 1 24.10 Malignant neoplasm of prostate,inactive Malig neop of prostate, inactive 1 25 Infertility TreatmentInfertility Treatment — 25.1 Contraceptive management Contraceptivemanagement 1 25.2 Infertility female Infertility female 2 25.3Procreative management Procreative management 1 25.4 Infertility maleInfertility male 1 26 Maternity-Related Conditions Maternity-RelatedCond — 26.1 Abnormal product of conception Abnorm product of conception1 26.2 Ectopic pregnancy Ectopic pregnancy 2 26.3 Spontaneous andinduced abortions Spont and induced abortions 1 26.4 Single newborn,normal pregnancy Single newborn, normal 1 26.5 Single newborn,complicated pregnancy Single newborn, complicated 3 26.6 Multiplenewborns, normal pregnancy Multiple newborns, normal 1 26.7 Multiplenewborns, complicated pregnancy Multiple newborns, complic 3 26.8 Otherobstetrical care Other obstetrical care 1 26.9 Completely normaldelivery Completely normal delivery 1 26.10 Multiple gestation Multiplegestation 1 26.11 Complications before birth Complications before birth3 26.12 Complications of delivery Complications of delivery 3 27Neonatal Conditions Neonatal Conditions — 27.1 Other minor neonatalconditions Minor neonatal conditions 3 27.2 Perinatal jaundice Perinataljaundice 3 27.3 Other major neonatal conditions Major neonatalconditions 3 27.4 Respiratory distress syndrome Respiratory distresssyndrome 1 27.5 Disorders due to short gestation Disorders to shortgestation 3 28 Congenital Anomalies Congenital Anomalies — 28.1Congenital anomalies of sense organs Cong anom of sense organs 3 28.2Congenital endocrine and metabolic anomaly Cong endo/metabolic anom 128.3 Congenital reproductive system anomaly Cong reproductive sys anom 128.4 Other chromosomal anomaly Other chromosomal anomaly 1 28.5 Down'ssyndrome Down's syndrome 1 29 Skin and Subcutaneous Tissue ConditionsSkin & Subcutaneous Tissue — 29.1 III-defined integument symptomsIII-defined integument sym 1 29.2 Congenital anomalies of skinCongenital anomalies of skin 1 29.3 Congenital integument anomaly Congintegument anom 1 29.4 Other infections of skin and subcutaneous Otherinf skin/subcutan tissue 2 tissue 29.5 Other disorders of skin andsubcutaneous Other dsdr skin/subcutan tiss 3 tissue 29.6 Skin keratosesSkin keratoses 2 29.7 Impetigo Impetigo 1 29.8 Urticaria Urticaria 129.9 Dermatitis and eczema Dermatitis and eczema 2 29.10 Cellulites andabscess, finger and toe Cellul & abscess, finger/toe 2 29.11 Cellulitesand abscess, leg and buttock Cellul & abscess, leg/buttock 1 29.12Cellulites and abscess, other site Cellul & abscess, other site 1 29.13Rosacea Rosacea 1 29.14 Dermatophytoses Dermatophytoses 2 29.15Sebaceous cyst Sebaceous cyst 1 29.16 Pilonidal cyst Pilonidal cyst 229.17 Acne Acne 1 29.18 Lipoma Lipoma 2 29.19 Benign neoplasm of skinBenign neoplasm of skin 1 29.20 Diseases of nail, excluding infectionsDz of nail, excluding infections 1 29.21 Diseases of hair and hairfollicles Dz of hair and hair follicles 2 29.22 Erythematous conditionErythematous condition 2 29.23 Psoriasis and pityriasis Psoriasis andpityriasis 2 29.24 Carcinoma in situ of skin Carcinoma in situ of skin 129.25 Chronic skin ulcer Chronic skin ulcer 2 29.26 Other malignancy ofskin Other malignancy of skin 2 29.27 Kaposi's sarcoma Kaposi's sarcoma3 29.28 Malignant melanoma of skin, initial Malig melanoma of skin,initial 2 29.29 Malignant melanoma of skin, active Malig melanoma ofskin, active 2 29.30 Malignant melanoma of skin, follow up Maligmelanoma of skin, fup 2 30 Breast Conditions Breast Conditions — 30.1Inflammatory disease of breast Inflammatory disease of breast 2 30.2Cystic breast disease Cystic breast disease 2 30.3 Benign neoplasm ofbreast Benign neoplasm of breast 1 30.4 Carcinoma in situ of breast,initial Carc in situ of breast, initial 1 30.5 Carcinoma in situ ofbreast, active Carc in situ of breast, active 1 30.6 Carcinoma in situof breast, follow-up Carc in situ of breast, fup 1 30.7 Malignantneoplasm of breast skin Malig neop of breast skin 1 30.8 Malignantneoplasms of breast, initial Malig neop of breast, initial 2 30.9Malignant neoplasm of breast, active Malig neop of breast, active 230.10 Malignant neoplasm of breast, follow-up Malig neop of breast, fup2 31 Musculoskeletal Conditions Musculoskeletal Conditions — 31.1Congenital musculoskeletal anomaly Cong musculoskel anomaly 1 31.2Congenital anomalies of spine Congenital anomalies of spine 3 31.3 Otherarthropathy disorders Other arthropathy disorders 3 31.4 BursitisBursitis 3 31.5 Other disorders of bone and cartilage Other dsdr bone &cartilage 3 31.6 Nonallopathic lesions Nonallopathic lesions 2 31.7 Bonetransplant Bone transplant 1 31.8 Cervical spine pain Cervical spinepain 3 31.9 Low back pain Low back pain 3 31.10 Other acquired deformityOther acquired deformity 2 31.11 Other curvature of spine Othercurvature of spine 2 31.12 Scoliosis Scoliosis 1 31.13 Minor injury oftrunk Minor injury of trunk 1 31.14 Osteoporosis Osteoporosis 1 31.15Benign neoplasm of skull and trunk bones Benign neop skull/trunk bones 131.16 Other osteochondropathies Other osteochondropathies 1 31.17Osteomyelitis Osteomyelitis 3 31.18 Diffuse connective tissue disordersDiffuse connective tiss dsdr 1 31.19 Rheumatoid arthritis Rheumatoidarthritis 3 31.20 Dislocation of vertebra Dislocation of vertebra 331.21 Fracture of vertebra Fracture of vertebra 3 31.22 Major injury oftrunk Major injury of trunk 1 31.23 Traumatic pneumothorax Traumaticpneumothorax 3 31.24 Crushing injury of trunk Crushing injury of trunk 231.25 Malignant neoplasm of skull and trunk bones Malig neop skull/trunkbones 1 32 Upper Limb Conditions Upper Limb Conditions — 32.1 Contusionof upper limb Contusion of upper limb 2 32.2 Sprain/strain of wrist andfinger Sprain/strain of wrist & finger 2 32.3 Sprain/strain of upper armSprain/strain of upper arm 2 32.4 Sprain/strain of lower armSprain/strain of lower arm 2 32.5 Open wound of hand and fingers Openwound hand & fingers 3 32.6 Open wound of arm Open wound of arm 3 32.7Dislocation of finger and wrist Dislocation of finger and wrist 3 32.8Dislocation of upper arm Dislocation of upper arm 3 32.9 Congenitaldeformities of upper limb Cong deformities upper limb 3 32.10 Benignneoplasm of upper limb Benign neop of upper limb 1 32.11 Fracture ofhand bones Fracture of hand bones 3 32.12 Amputation of fingerAmputation of finger 2 32.13 Fracture of radius and ulna Fracture ofradius and ulna 3 32.14 Fracture of humerus Fracture of humerus 3 32.15Fracture of clavicle and scapula Fracture of clavicle/scapula 3 32.16Amputation of hand and arm Amputation of hand and arm 3 32.17 Crushinginjury of upper limb Crushing injury of upper limb 3 32.18 Malignantneoplasm of upper limb Malig neop of upper limb 1 33 Lower LimbConditions Lower Limb Conditions — 33.1 Contusion of lower limbContusion of lower limb 2 33.2 Sprain/strain of foot and ankleSprain/strain of foot and ankle 2 33.3 Sprain/strain of legSprain/strain of leg 3 33.4 Sprain/strain of hip and thigh Sprain/strainof hip and thigh 1 33.5 Open wound of foot and toes Open wound of footand toes 3 33.6 Open wound of leg Open wound of leg 3 33.7 Open wound ofhip and thigh Open wound of hip and thigh 3 33.8 Dislocation of foot andankle Dislocation of foot and ankle 3 33.9 Dislocation of kneedislocation of knee 2 33.10 Dislocation of hip Dislocation of hip 333.11 Congenital deformities of lower limb Cong deformities lower limb 333.12 Joint replacement Joint replacement 1 33.13 Benign neoplasm oflower limb Benign neop of lower limb 1 33.14 Hammer toe Hammer toe 333.15 Degenerative joint disease Degenerative joint disease 2 33.16Fracture of foot bones Fracture of foot bones 3 33.17 Fracture of ankleFracture of ankle 3 33.18 Fracture of patella Fracture of patella 233.19 Fracture of tibia and fibula Fracture of tibia and fibula 3 33.20Amputation of toes Amputation of toes 2 33.21 Other joint derangementOther joint derangement 3 33.22 Derangement of knee Derangement of knee3 33.23 Fracture of femur Fracture of femur 3 33.24 Amputation of footand leg Amputation of foot and leg 3 33.25 Crushing injury of lower limbCrushing injury of lower limb 3 33.26 Malignant neoplasm of lower limbMalig neoplasm of lower limb 1 34 Mental Disorders Mental Disorders —34.1 Other nonpsychotic disorders Other nonpsychotic disorders 3 34.2Psychogenic conditions Psychogenic conditions 3 34.3 Sleep walking Sleepwalking 1 34.4 Hypersomnia Hypersomnia 1 34.5 Insomnia Insomnia 2 34.6Other neurotic disorders Other neurotic disorders 1 34.7 Maltreatmentsyndrome Maltreatment syndrome 1 34.8 Sexual deviations Sexualdeviations 1 34.9 Tics and repetitive movements Tics and repetitivemovements 3 34.10 Hysteria Hysteria 3 34.11 Delays in metal developmentDelays in mental development 2 34.12 Phobic disorders Phobic disorders 234.13 Anxiety disorders Anxiety discords 2 34.14 Personality anddisturbance disorder Personality & disturb dsdr 3 34.15 Other nonorganicpsychoses Other nonorganic psychoses 1 34.16 Other eating disordersOther eating disorders 1 34.17 Nonpsychotic depression Nonpsychoticdepression 2 34.18 Obsessive-compulsive disorders Obsessive-compulsivedsdr 1 34.19 Paranoid states Paranoid states 2 34.20 Sleep apnea Sleepapnea 1 34.21 Major depression Major depression 3 34.22 Mentalretardation Mental retardation 2 34.23 Manic depression Manic depression3 34.24 Bipolar depression Bipolar depression 3 34.25 Bulimia Bulimia 134.26 Anorexia nervosa Anorexia nervosa 1 34.27 Autism Autism 1 34.28Narcolepsy Narcolepsy 1 34.29 Alcohol dependence Alcohol dependence 334.30 Drug dependence Drug dependence 3 34.31 Organic dementias Organicdementias 3 34.32 Schizophrenia Schizophrenia 3 34.33 Alzheimer'sdisease Alzheimer's disease 1 35 Burns Burns — 35.1 Burn of upper limbBurn of upper limb 3 35.2 Burn of lower limb Burn of lower limb 3 35.3Burns of head and neck Burns of head and neck 3 35.4 Burn of trunk Burnof trunk 3 35.5 Burn of multiple sites Burn of multiple sites 3 36 OtherMedical Conditions Other Medical Conditions — 36.1 Complication ofsurgery Complication of surgery 1 36.2 Complication of genitourinaryprocedure Complic genitourin procedure 1 36.3 Complication of orthopedicprocedure Complic orthopedic procedure 1 36.4 Complication ofgastrointestinal procedure Complic gastrointestinal proc 1 36.5Complication of respiratory procedure Complic respiratory procedure 136.6 Complications of trauma Complications of trauma 1 36.7 Complicationof nervous system procedure Complic nervous sys proc 1 36.8 Complicationof vascular procedure Complic vascular procedure 1 36.9 Complication oftransplant Complication of transplant 1 36.10 Effects of external causesEffects of external causes 1 36.11 Poisoning by medicines Poisoning bymedicines 1 36.12 Toxic effects of substances Toxic effects ofsubstances 1 36.13 Personal assaults Personal assaults 1 36.14 Motorvehicle accident Motor vehicle accident 1 36.15 General presentingsymptoms General presenting symptoms 1 36.16 Non-specific exanthemNon-specific exanthem 1 36.17 Abdominal pain Abdominal pain 1 36.18Dyspnea Dyspnea 2 36.19 Chest pain Chest pain 1 36.20 Non-newbornjaundice Non-newborn jaundice 1 36.21 Non-newborn cyanosis Non-newborncyanosis 1 36.22 Shock Shock 1 36.23 Spleenomegaly Spleenomegaly 1 36.24Hepatomegaly Hepatomegaly 1 36.25 Coma and stupor Coma stupor 1 36.26Gangrene Gangrene 1 37 Replaced Diagnosis Codes Replaced Diagnosis Codes— 37.1 Replaced non-specific diagnosis codes Replaced non-specific dxcode 1

An embodiment of the present invention forms longitudinal episodes ofcare for a patient using medical claims data. A longitudinal episode ofcare is defined as all services linked together that are used to treat apatient's medical condition within a specified period of time, includingall ambulatory, outpatient, inpatient, and prescription drug experience.This linkage allows examination of a physician's (or a physiciangroup's) global patterns of treatment for a patient with a specificcondition, such as diabetes and arthritis. The longitudinal episode ofcare may also be used in patient disease management, patient healthpromotion and wellness, and many other healthcare programs.

Acute Episodes of Care

An acute episode of care has a finite duration and is defined by aspecified time period, or window period. An embodiment of the presentinvention has three types of window periods for acute episodes of care.

Dynamic Window Period:

The specified time period, or window period, is based on the maximumnumber of days between contact with a provider for which follow-up careis still reasonable. Each of the medical conditions has its uniquedynamic window period. If the date of service for a patient's episode isseparated by a longer period than the dynamic window period, the latestdate of service considered the start date for a new condition-specificepisode of care.

For example, as shown in FIG. 3, the dynamic window period for MedicalCondition 9.1-upper respiratory infections is 60 days. Assume that apatient had three services in January and two services in August of thesame calendar year. Because the services in the series were separated bymore than 60 days, these would be two episodes of care. Table 11A givesthe dynamic window periods for medical conditions in PMC Group9-Respiratory Conditions.

TABLE 11A Medical Condition Dynamic Window Periods for PMC Group9-Respiratory Conditions Medical Condition Medical Condition WindowNumber Long Description Periods 6 Ear conditions — 6.1 Otitis externa 906.2 Wax in ear 60 6.3 Open wound of ear 90 6.4 Other disorders of ear 906.5 Otitis media 90 6.6 Disorders of tympanic 120 membrane 6.7 Disordersof middle ear 120 6.8 Vertiginous syndromes 180 6.9 Mastoiditis 180 6.10Hearing loss 365 6.11 Malignant neoplasm of 365 middle earStatic Window Period:

The specified time period, or window period, is based on the maximumnumber of days after contact with a provider for which follow-up care isstill reasonable. Each of the medical conditions has its unique staticwindow period. From the initial date of service for a patient's episode,the static window period defines the fixed number of days to count fromthe initial date of service to define all services to include in theepisode of care. Then, if another medical condition-specific service isobserved for the same patient after the fixed number of window perioddays, this service is considered the start date for a new secondcondition-specific episode of care. For the second episode of care, thestatic window period defined fixed number of days is again applied.

For example, as shown in FIG. 4, the static window period for MedicalCondition 9.1 upper respiratory infections is 40 days. Assume that apatient had three services in January, the first on January fifth (5th),and two services in August in the same calendar year, the initialservice on August tenth (10th). The three services in January werewithin the static 40 day window period from the initial service onJanuary fifth (5th); this is because 40 days to count out from Januaryfifth (5th) is about February fourteenth (14th). Therefore, these threeservices are in the first episode of care. Then, the second episode ofcare begins on August tenth (10th), and 40 days are counted out fromAugust tenth (10th). Therefore, the two services in August are in thesecond episode of care. Table 11B gives the static widow periods formedical conditions in PMC Group 9-Respiratory Conditions.

TABLE 11B Medical Condition Static Window Periods for PMC Group9-Respiratory Conditions Medical Static Condition Medical ConditionWindow Number Long Description Periods 6 Ear conditions — 6.1 Otitisexterna 60 6.2 Wax in ear 40 6.3 Open wound of ear 60 6.4 Otherdisorders of ear 60 6.5 Otitis media 60 6.6 Disorders of tympanic 80membrane 6.7 Disorders of middle ear 80 6.8 Vertiginous syndromes 1206.9 Mastoiditis 120 6.10 Hearing loss — 6.11 Malignant neoplasm of —middle earVariable Window Period:

The specified time period, or window period, is based on the maximumnumber of days after contact with a provider for which follow-up care isstill reasonable. Each of the medical conditions has its unique variablewindow period. From the initial date of service for a patient's episode,the window period defines the fixed number of days to count from theinitial date of service to define all services to include in the episodeof care. Then, if another medical condition-specific service is observedfor the same patient after the fixed number of window period days, thisservice is considered the start date for a new second condition-specificepisode of care. The fixed number of window period days is extended by aset number of days for each reoccurrence of a medical condition-specificepisode of care.

For example, as shown in FIG. 5, the window period for the initialepisode of Medical Condition 9.1 upper respiratory infections is 40days. Assume that a patient had three services in January, the first onJanuary fifth (5th), and two services in August in the same calendaryear, the initial service on August tenth (10th). The three services inJanuary were within the 40 day window period from the initial service onJanuary fifth (5th); this is because 40 days to count out from Januaryfifth (5th) is about February fourteenth (14th). Therefore, these threeservices are in the first episode of care. Then, the second episode ofcare begins on August tenth (10th), and the window period is extended by8 days and therefore, 48 days are counted out from August tenth (10th).Therefore, the two services in August are in the second episode of care.

Chronic Episodes of Care

A chronic episode of care by definition is ongoing and once started willgo on indefinitely. Therefore, chronic episodes of care have no windowperiod associated with them and the user may define a desired fixedduration for Chronic Episodes of Care. For example, Medical condition10.2 Hypertension or Medical Condition 9.11 Asthma have no window periodand once an episode of Hypertension or Asthma starts, it will continueon indefinitely. In an embodiment, to calculate physician efficiency,chronic episodes may have a finite duration and end after 180 days or365 days.

Step 100: Form Inpatient Encounters and Assign Diagnosis

The Grouper function first checks professional service CLIs forinpatient facility place of service to identify potential inpatientencounters. A professional service includes the Types of Service ofvisits, lab/path services, medical and surgical procedures, anddiagnostic tests. All facility charges and prescription drugs areexcluded from professional services. The professional services occur ina Place of Service of hospital inpatient.

The identification of a professional service that starts a potentialinpatient encounter is called a trigger event.

The rule associates with the potential inpatient encounter all servicesthat occurred on the dates following the trigger event. Servicescontinue to be counted until an end date is reached. The end date isidentified when there is a two-day gap in professional charges. At thispoint the potential encounter ends. For example, if one CLI ends on aMonday and the next CLI begins on Wednesday, then the two CLIs could bepart of a single inpatient encounter because only one day (Tuesday)separates them. If the second CLI begins on Thursday, then it would bepart of a separate inpatient encounter because two days (Tuesday andWednesday) separate it from the first CLI.

The rule then looks at all professional service charges associated withthe potential inpatient encounter to determine whether they total $350or more. If the professional service charges total $350 or more, therule concludes that we have identified an eligible inpatient encounter.Experience shows that charges should almost always be over this minimumthreshold level. The minimum threshold level is subject to change overtime.

For inpatient encounters with professional service charges of $350 ormore, the rule assigns a diagnosis code to all CLIs associated with theencounter. To assign the appropriate diagnosis code, all professionalservice CLIs associated with the encounter are identified. The rule thentemporarily assigns these professional service CLIs to one of 526medical conditions. Using these temporary assignments, the rule adds upall charges by medical condition. The medical condition with the highestcharge amount is then assigned as the medical condition for the entireencounter, and all CLIs associated with the encounter receive diagnosiscodes appropriate for that medical condition.

The rule uses professional charges to identify the start and end datesof a hospital inpatient encounter. Facility services (i.e., room andboard service and ancillary services) are assigned to the ongoingencounter using these start and end dates.

Step 120: Drop Inpatient Encounters without Minimal Professional Charges

If the overall professional service charges associated with thepotential encounter do not reach $350, then an eligible inpatientencounter has not been identified. For example, consider a cardiacstress test that includes physician charges of $250 marked withinpatient facility as the place of service and a facility-relatedcomponent of $300. Broken down in this way, we can see that the medicalcharges (non-facility and drug charges) do not meet the $350 threshold,and the potential encounter would not be regarded as an eligibleinpatient encounter. When the potential encounter does not meet the $350threshold, all CLIs associated with the potential inpatient encounterare released and will be examined as described in the next step.

Step 130: Form Outpatient Encounters and Assign Diagnosis

To identify outpatient facility encounters, the Grouper functionexamines all professional service CLIs except those already assigned toan inpatient facility encounter. The rule looks for professional serviceCLIs that have a Place of Service of inpatient hospital, emergency room,urgent care, outpatient facility, surgicenter, or birthing center as theplace of service. At this point in the process, the professional serviceCLIs with a Place of Service of inpatient hospital did not meet theminimum hospital inpatient encounter criteria. These CLIs are nowexamined for a possible outpatient facility encounter.

The identification of a professional service that starts a potentialoutpatient encounter is called a trigger event. CLIs with Provider Typeservices that include only laboratory and durable medical equipment donot trigger a potential outpatient encounter.

Once a potential outpatient encounter has been identified, the ruleinspects all CLIs that occurred on the date of the potential encounterto determine whether total charges equal or exceed $100. If so, then therule concludes that an eligible outpatient encounter has beenidentified. Experience shows that charges should almost always be overthis minimum threshold level. The minimum threshold level is subject tochange over time.

For outpatient encounters with total charges of $100 or more, the ruleassigns a diagnosis code to all CLIs associated with the encounter. Toassign the appropriate diagnosis code, all professional service CLIsassociated with the encounter are identified. The rule then temporarilyassigns these professional service CLIs to one of 526 medicalconditions. Using these temporary assignments, the rule adds up allcharges by medical condition. The medical condition with the highestcharge amount is then assigned as the medical condition for the entireencounter, and all CLIs associated with the encounter receive diagnosiscodes appropriate for that medical condition.

Step 140: Drop Outpatient Encounters without Minimal Total Charges

If the total charges are less than $100, the rule concludes that that wehave not identified an actual outpatient encounter. For example, manylabs are performed in outpatient hospital facilities. This analysishelps ensure that lab-only events are not included as outpatientencounter.

CLIs associated with potential outpatient encounters that do not meetthe $100 threshold may still be associated with medical conditionepisodes. They are released and through subsequent analysis may beassigned to the following service categories: Professional Visits,Diagnostic Tests, Laboratory and Pathology, Medical and SurgicalProcedures, Prescription Drugs, Alternative Sites, or Other MedicalServices.

Facility CLIs not associated with actual inpatient or outpatientencounters are assigned to other medical care service categories basedprimarily on the procedure code that may be present on the CLI. Forexample, if the procedure code indicates chemotherapy, it would beassigned to the service category Other Medical Services as part of thesub-service category Chemo/Radiology. If no explanatory procedure codeis present, the facility CLI will be categorized under the servicecategory Other Medical Services as part of the sub-service categoryOther Medical Care.

Step 150: Ill-Defined Diagnosis Code Rule

A patient's medical service will appear in an episode of care if theclaim line item (CLI) has a valid and “defined” assigned ICD.9 code. Forexample, defined codes include ICD.9 codes such as 250.0 (diabeteswithout mention of complication), 244.3 (iatrogenic hypothyroidism), and370.20 (superficial keratitis).

However, up to 40% of all CLIs may have “ill-defined” assigned ICD.9codes. Ill-defined means that either the ICD.9 codes are either missingor nonspecific ICD.9 codes. Nonspecific codes include ICD.9 codes suchas 780.9 (other general symptoms), 796.4 (other abnormal clinicalfindings), and 799 (other ill-defined causes of morbidity). Non-specificcodes are treated as if the ICD.9 code on the CLI is missing. The CLIremains, but the ill-defined value on the CLI is ignored. Ill-definedICD.9 coding falls into medical condition 37.1.

To prevent under-reporting of utilization within an episode of care, adefined ICD.9 code is assigned to CLIs with ill-defined ICD.9 codes.Consequently, the Ill-Defined Diagnosis Code Rule assigns a diagnosiscode to each CLI with an ill-defined code as follows.

The Grouper function first looks for an appropriate diagnosis during thetwo days before and after the non-specific diagnosis code date. Forexample, assume a CLI has a non-specific diagnosis code on March 17. Therule looks backwards two days until March 15 for a valid and accuratediagnosis code. If no defined diagnosis code is found, then the rulelooks two days forward until March 19 for a valid accurate diagnosiscode. If no appropriate diagnosis is found, the rule then examines thefive days before and after. If no appropriate diagnosis is found, therule then examines the nine days before. In an embodiment, nine daysforward in time can be examined and day period durations and number canbe changed.

Moreover, the expected resource intensity level of each of 526 medicalconditions is considered. If there are two separate CLIs on a given daythat have a defined ICD.9 code, the rule assigns the diagnosis code ofthe more resource-intensive medical condition to the CLI with anill-defined code. For example, if there is a diagnosis code for diabeteson February 15 and also a diagnosis code for upper respiratory tractinfection on February 15, then diabetes will be assigned because it ismore resource intensive. So, if there are two CLIs on the same day withdifferent ICD.9 codes in the primary position field, then the mostresource intensive diagnosis code is assigned during the two daylook-back assignment process, during the two day look-forward assignmentprocess, and so forth.

Table N shows the resource intensity rank order assigned to differentmedical conditions. The lower the resource intensity rank number for amedical condition, the higher the expected need for medical careservices as compared to medical conditions with higher resourceintensity rank numbers.

TABLE N Resource Intensity Rank Order for Medical Conditions MedicalResource Condition Medical Condition Intensity Number Long DescriptionRank 6 Ear Conditions — 6.1 Otitis externa 464 6.2 Wax in ear 459 6.3Open wound of ear 457 6.4 Other disorders of ear 455 6.5 Otitis media454 6.6 Disorders of tympanic membrane 450 6.7 Disorders of middle ear449 6.8 Vertiginous syndromes 440 6.9 Mastoiditis 436 6.10 Hearing loss192 6.11 Malignant neoplasm of middle ear  84 22 Urinary Tract andKidney Conditions — 22.1 Other disorders of urethra 428 22.2 Congenitalanomalies of bladder and 413 urethra 22.3 Urinary tract infections 41222.4 Urethritis 411 22.5 Urethral stricture 410 22.6 Other disorders ofbladder 397 22.7 Kidney infection 396 22.8 Hydronephrosis 335 22.9Congenital anomalies of kidney and ureter 334 22.10 Disorders of kidneyand ureter 140 22.11 Calculus of kidney and ureter 132 22.12Glomerulonephritis 130 22.13 Bladder transplant  57 22.14 Renal dialysis 49 22.15 Renal failure  50 22.16 Kidney transplant, initial  46 22.17Kidney transplant, follow-up Not applicable 22.18 Malignant neoplasm ofbladder and urethra  25 22.19 Malignant neoplasm of kidney and ureter 20

If a CLI has not been assigned to a valid ICD.9 code at this point, thenthe CLI will not be assigned to an episode of care at this point intime.

Prescription drug CLIs generally do not have an ICD.9 diagnosis codeassigned. An embodiment of the present invention assigns a defined ICD.9diagnosis code to each prescription drug CLI by applying the sameIll-Defined Diagnosis Code Rule as for any other service category thathas an ill-defined ICD.9 code.

Step 160: Trigger Episode of Care Building

A Grouper function treats the start and end points for chronic and acuteepisodes differently. For chronic conditions (e.g., diabetes, asthma,ischemic heart disease), an episode of care begins when a CLI isinitially found during the study period that has a defined ICD.9 codethat has been assigned to that medical condition. Then, chronicconditions may continue on indefinitely as recognized by the windowperiod of 365 days (refer to Table 11 for chronic disease window periodsof 365 days).

However, for the purposes of physician efficiency analysis, chronicconditions are considered to be 180-day duration. Therefore, a chroniccondition ends 180 days after identifying the first CLI with a diagnosis(defined ICD.9 code) for the specific chronic condition. The ruledetermines that the patient is present for 180 days during the studyperiod after the first CLI with a diagnosis for the specific chroniccondition. Moreover, in the physician efficiency analysis, all chronicconditions included in the analysis must start before the last day ofthe first half of the study period and must have a 180-day duration. Theembodiment recognizes that this maximum allowable duration may bevaried.

For acute conditions (e.g., upper respiratory infections, otitis media,conjunctivitis), an episode of care begins when a CLI is initially foundduring the study period that has a defined ICD.9 code that has beenassigned to that medical condition.

For acute conditions, the patient's episode duration directly relates tothe process of care. The process of care is identified using windowperiods for each medical condition. A medical condition's window periodis based on the maximum number of days between contact with a providerfor which follow-up care is still reasonable. Each medical condition hasits own unique window period as presented for select medical conditionsin Table 11. If the date of service for a patient's episode is separatedfrom the previous date of service by a period longer than the windowperiod for that condition, the latest date of service is considered thestart date for a new condition-specific episode of care.

For example, upper respiratory infections generally last up to 30 days.The window period is made about 1.5-to-2.5 times as long as the expectedaverage longer duration episodes for a medical condition to ensureepisode completion. Therefore, the window period for upper respiratoryinfections is about 60 days. Acute condition episodes are consideredcomplete (or end) if an amount of time (equal to the window period)elapses in which no ICD.9 codes for that condition are present.

Continuing our upper respiratory infection example, assume that apatient had three treatments for upper respiratory infection in Januaryand two in the following August. The window period for upper respiratoryinfections is 60 days. Because the two groups of treatments wereseparated by more than 60 days, they would be considered two separateepisodes of care. In the physician efficiency analysis, the maximumallowable duration for any acute condition is 180 days. The embodimentrecognizes that this maximum allowable duration may be varied.

Step 170: Apply Rank Order Rule

After the triggering episode of care building rule, the rank order ruleassigns claims that continue to have ill-defined diagnosis codes (e.g.,missing or non-specific ICD.9 codes) to the highest resource-intensityranked ongoing episode for a patient. Table N presents the resourceintensity rank order for select medical conditions.

After the rank order rule, generally more than 98% of CLIs receive adefined ICD.9 code, and are assigned to one of the patient's ongoingcondition-specific episodes of care. However, the percent rangesgenerally from 85% to 99% of CLIs that receive a defined ICD.9 code,depending on the accuracy of original ICD.9 coding in the particularmedical claims data file of being examined.

Step 180: Apply CLI Day Rule

The Grouper function next examines the more resource-intensive medicalcondition episodes to ensure an appropriate number of CLIs are presentwithin the episode of care. This is to ensure that no episodes are builtbecause of a single CLI ICD.9 miscoding by a physician.

Most episodes, after being built, are eligible using the requirementthat only one CLI is present with a condition-specific ICD.9 diagnosiscode. For example, Table 12 shows that only one CLI with an ICD.9 codeis required for conditions such as neuritis, headaches, conjunctivitis,otitis media, sinusitis, and upper respiratory infections.

However, some episodes, after being built, are eligible using therequirement that a CLI with a condition-specific ICD.9 code must bepresent on two different days. These are episodes of medical conditionsthat can be expected to last more than one day. For instance, the oneCLI on two different days rule is required for conditions such asmyoneural disorder, multiple sclerosis, pneumothorax, pneumocystosis,fracture of skull, intestinal obstruction, hepatitis, fracture ofvertebra, and deep burns.

Other episodes, after being built, are eligible using the requirementthat a CLI with a condition-specific ICD.9 code must be present on threedifferent days. These episodes are more chronic by nature and requiremore resource intensive treatment. For example, the one CLI on threedifferent days rule used for conditions such as injury of the spinalcolumn, malignant neoplasm of nasal cavities, malignant neoplasm oflung, cerebrovascular hemorrhage, malignant neoplasm of pancreas, andrenal failure.

If the built episode does not meet the required eligibility criteria,then the CLIs in the episode are released and through subsequentanalysis, may be assigned to another of the patient's ongoing episodesof care. The diagnosis coding on the released CLIs is treated the sameway as if the ICD.9 code were “μl-defined.”

TABLE 12 Claim Line Item (CLI) Day Rule Table Medical CLI ConditionMedical Condition Day Number Long Description Rule 6 Ear Conditions —6.1 Otitis externa 1 6.2 Wax in ear 1 6.3 Open wound of ear 1 6.4 Otherdisorders of ear 1 6.5 Otitis media 1 6.6 Disorders of tympanic membrane1 6.7 Disorders of middle ear 1 6.8 Vertiginous syndromes 1 6.9Mastoiditis 1 6.10 Hearing loss 1 6.11 Malignant neoplasm of middle ear3 16 Thyroid Disorders — 16.1 Other disorders of thyroid 1 16.2 Goiter 116.3 Hypothyroidism 1 16.4 Hyperthyroidism 2 16.5 Malignant neoplasm ofthyroid 3 22 Urinary Tract and Kidney Conditions — 22.5 Urethralstricture 1 22.6 Other disorders of bladder 1 22.7 Kidney infection 122.8 Hydronephrosis 1 22.9 Congenital anomalies of kidney and ureter 122.10 Disorders of kidney and ureter 1 22.11 Calculus of kidney andureter 1 22.12 Glomerulonephritis 1 22.13 Bladder transplant 3 22.14Renal dialysis 3 22.15 Renal failure 3 22.16 Kidney transplant, initial3 22.17 Kidney transplant, follow-up 3 22.18 Malignant neoplasm ofbladder and urethra 3 22.19 Malignant neoplasm of kidney and ureter 3Step 190: Apply Rank Order Rule

After the CLI day rule, the rank order rule is reapplied in an attemptto assign CLIs, which were released during the CLI day rule, a defineddiagnosis code as defined under Step 170. The ill-defined CLIs areassigned to the highest resource-intensity ranked ongoing episode for apatient that has passed the CLI day rule.

Step 200: Severity-of-Illness Assignment Rule

Each patient's condition-specific episode is labeled with aseverity-of-illness marker to reduce the heterogeneity of episodeswithin a medical condition. Severity-of-illness is defined as theprobability of loss of function due to the physiologic progression orimpact of the medical condition. Under this definition, the Grouperfunction uses only ICD.9 diagnosis codes to assign a patient's episodewith a severity-of-illness marker. The Grouper function does not defineseverity-of-illness by resource utilization within the patient'scondition-specific episode (such as whether a surgery or aresource-intensive diagnostic test was present in the patient's episodeof care).

There are up to three (3) severity-of-illness (SOI) classes for each ofthe 526 medical conditions, with SOI-1 being the least severe (routine,noncomplicated) and SOI-3 being the most severe. However, the embodimentrecognizes that there may be a differing number of SOI classes. Somemedical conditions have only one or two severity-of-illness levels.Refer to the fourth column in Table 10, List of Medical Conditions inthe Grouper function.

The severity-of-illness assignment rule operates to increase the SOIclass on a patient's medical condition episode on the basis of two maincriteria: (1) the ICD.9 codes that are present on the CLIs in eachepisode with respect to SOI class; and (2) the number of CLIs with ICD.9codes in the more severe SOI classes.

With respect to the first criterion, Table 13 shows the selecteddiagnosis (ICD.9) codes listed in Table M stratified by SOI class. TheICD.9 codes within each SOI class are stratified based on theprobability of loss of function due to the physiologic progression ofthe medical condition. A patient's episode may receive a more severe SOIranking only if CLIs within the episode have ICD.9 coding present in themore severe SOI classes. For each medical condition episode of care, theseverity-of-illness assignment rule accesses this table and determineswhether the appropriate ICD.9 coding is present for a potential increasein SOI ranking.

TABLE 13 Selected Diagnosis (ICD.9) Codes by Medical Condition andSeverity-of-Illness Level Medical Number of Condition Medical ConditionSeverity SO1-1 SO1-2 SO1-3 Number Long Description Classes Class ClassClass 5.2 Conjunctivitis 2 077.0 372.1 — 077.8 372.14 372.0 372.22372.01 6.5 Otitis media 3 381 381.20 382.01 381.02 382 382.1 381.06382.00 382.4 7.2 Sinusitis 2 461.0 473 — 461.2 473.2 461.3 473.3 9.11Asthma 3 493.0 493.01 493.21 493.02 493.2 493.1 10.2 Hypertension 3401.1 402 402.11 405.1 402.0 404.01 403.00 404.11 403.1 405.0

With respect to the second criterion, Table 14 shows the minimum numberof CLIs with required ICD.9 codes in the more severe SOI classes. Foreach medical condition episode of care, the severity-of-illnessassignment rule accesses this table and determines the number of CLIswith required ICD.9 codes. If the number of CLIs with required ICD.9codes is not achieved, then the patient's condition-specific episodewill remain in the less severe SOI class (e.g., SOI-1 class). Forexample, a patient's sinusitis episode will receive an SOI-2 rank onlyif the episode contains 6 or more CLIs (refer to Table 14) with theICD.9 codes listed in the sinusitis SOI-2 column of Table 13. Otherwise,the sinusitis episode will receive an SOI-1 rank.

TABLE 14 Number of CLIs with Required ICD.9 Codes in the More Severe SOIClasses Medical Number of Condition Medical Condition Severity SOI-1SOI-2 SOI-3 Number Long Description Classes Class Class Class 5.2Conjunctivitis 2 1 6 — 6.5 Otitis media 3 1 6 10 7.2 Sinusitis 2 1 6 —9.11 Asthma 3 1 6 10 10.2 Hypertension 3 1 6 10Step 210: Vertical Episode Merge Rule

Often the physiology of some medical conditions results in themanifestation of different symptoms. Depending on a patient's presentingsymptoms, a physician may code a patient's diagnosis under different,but somewhat correlated medical conditions. Considering physician codingalone can result in episodes that are fragmented and don't give a fullpicture of care received for a medical condition. The Grouper functionaddresses this situation using a technique called the vertical episodemerge rule.

For example, a physician may assign a patient to one of severalcardiovascular disease-related medical conditions: ischemic heartdisease, congestive heart failure, cardiac arrhythmia, hypertension, andother cardiovascular conditions. Likewise, presenting symptoms couldresult in a physician assigning a patient to one of severalrespiratory-related medical conditions: emphysema, chronic bronchitis,chronic obstructive pulmonary disease, asthma, and lower respiratoryinfections.

However, there usually is one underlying physiologic condition for apatient having several related medical conditions. To address thisissue, physician panels were formulated to determine which of apatient's condition-specific episodes should be combined and when. Thepanels developed algorithms for combining related condition-specificepisodes and assigning a patient to an overall medical condition episodebased on the underlying most resource-intensive physiologic condition.Within each PMC Group, the panels listed medical conditions in ascendingorder of expected resource intensity level and physiologic progressionof the condition or disease (from least resource intensive andphysiologic progression to the most resource intensive and physiologicprogression (refer to Table 10).

The vertical episode merge rule accesses Table 10 and merges a patient'scondition-specific episodes in the same PMC Group. The episodes mergedown the PMC Group medical condition list, always merging the patient'slesser resource intensity episodes into the most resource intensivemedical condition episode. For example, assume a patient has episodes ofischemic heart disease, hypertension, and angina pectoris. Table 10shows that ischemic heart disease is the more resource-intensive medicalcondition in PMC Group 10. Consequently, hypertension and anginapectoris are folded into the patient's ischemic heart disease episode.This indicates that remaining hypertension and angina pectoris episodesare derived from patients without ischemic heart disease.

Failure to consider a patient's underlying medical condition willdistort the accuracy of a physician's efficiency measurement. Forexample, in the above patient, episodes would be generated for ischemicheart disease, hypertension, and angina pectoris even though thepatient's angina and hypertension can be attributed to the underlyingcondition of ischemic heart disease. Consequently, utilizationexperience within the patient's ischemic heart disease episode would beunderstated. If the vertical episode merge rule did not exist forcombining related condition-specific episodes, then a patient's medicalcondition utilization would be understated and a physician's practicepattern efficiency measure would be inaccurate.

The vertical episode merge rule considers how much time separatesepisodes in the same PMC Group. For Episode #2 to be considered formerge to a previously occurring Episode #1, a CLI from Episode #2 musteither overlap Episode #1's duration time period or occur during thewindow period of Episode #1. In the vertical episode merge rule, anywindow period greater than 60 days is considered to be equal to 60 days.However, the embodiment recognizes that complete window period durationsmay exist.

FIG. 6 shows the vertical merge process for a patient's episodes ofischemic heart disease (10.13), angina pectoris (10.8), and hypertension(10.2). The episodes are merged together to form one episode of ischemicheart disease (10.13).

Step 220: Horizontal Episode Merge Rule

A patient may present with non-specific signs and symptoms before a morespecific medical condition is diagnosed and treated. Non-specificmedical conditions do not necessarily reflect a bodily system or organsystem. Instead, they can reflect signs and symptoms such as abdominalpain, chest pain, dyspnea, spleenomegaly, non-specific exanthem, andjaundice. Table 15 presents sample non-specific medical conditions.

A patient's non-specific medical condition episodes need to be mergedwith the patient's more specific, resource-intensive medical conditionepisodes. Otherwise, a patient's specific medical condition utilizationwould be understated and a physician's practice pattern efficiencymeasure would be inaccurate. The Grouper function addresses thissituation using a technique called the horizontal episode merge rule.

The Grouper function performs a horizontal episode merge when anon-specific medical condition episode overlaps a more specific medicalcondition episode. In order to be considered for horizontal episodemerge, episodes must overlap so that they have service days in common.As illustrated in FIG. 7, the episode overlap may occur towards thebeginning, middle, or end of the ongoing specific medical condition.Window periods between episodes are not considered for horizontalepisode merges. However, the embodiment recognizes that window periodsbetween episodes may exist.

The horizontal episode merge rule accesses Table 15 for eachnon-specific medical condition and merges the non-specific episodes intothe more specific medical conditions in the PMC Group order defined inthe table. The rule operates as follows. When a non-specific episode isidentified, examine the Horizontal Episode Merge Order by PMC Groupcolumns and attempt to merge the non-specific episode. The rule loopsover each PMC Group in the defined precedence order, starting with themedical condition number stated in Table 15. The embodiment recognizesthat the PMC Groups may change in order and number.

For example, for general presenting symptoms (36.15), the horizontalepisode merge rule attempts to merge the patient's non-specific episode(36.15) with medical conditions in PMC Group 9 (Respiratory Conditions),beginning with lower respiratory diseases (Medical Condition 9.3) andmoving down the list from 9.3 through 9.20. If no specific medicalcondition for the patient is found in PMC Group 9, then the rule loopsover to find a medical condition in PMC Group 10 (Heart and PulmonaryConditions), beginning with ventricular arrhythmias (Medical Condition10.4). The rule moves down the medical condition list from 10.4 through10.25. If no specific medical condition for the patient is found in PMCGroup 10, then the rule loops over to find a medical condition in PMCGroup 13 (Digestive System Conditions).

The process continues on until either the non-specific episode (36.15)is merged with a more specific episode, or the precedence ordered PMCGroups are exhausted, and no horizontal episode merge occurs. If nomerge occurs, then the patient's non-specific episode (36.15) remains asgeneral presenting symptoms.

TABLE 15 Selected Non-Specific Medical Conditions Medical HorizontalEpisode Merge Order by PMC Group Condition Medical Condition (ConditionListed Indicates Start Point for Merge) Number Abbrev Description 1 2 34 5 6 7 8 9 10 2.1 Intestinal infections 3.1 20.5 — — — — — — — — 2.2Other bacteria diseases 3.1 9.10 21.3 20.1 22.12 13.19 35.1 23.3 24.510.14 36.1 Complication of surgery 21.3 31.17 33.5 32.5 10.4 11.8 14.135.1 12.1 24.5 36.15 General presenting symptoms 9.3 10.4 13.10 3.1 17.115.1 16.3 18.1 19.5 4.8 36.16 Non-specific exanthem 29.4 3.1 9.1 31.17.1 20.1 15.7 10.4 11.2 17.4 36.17 Abdominal pain 13.4 15.3 26.1 14.122.5 12.1 23.3 25.2 17.1 34.4 36.18 Dyspnea 9.1 10.14 3.1 7.2 8.1 4.821.3 31.17 34.4 — 36.19 Chest pain 10.4 9.10 3.1 21.3 34.4 30.8 31.1730.2 — — 36.20 Non-newborn jaundice 15.1 13.10 3.1 31.17 21.3 20.1 19.5— — — 36.23 Spleenomegaly 20.1 21.3 3.1 31.17 19.5 — — — — — 36.24Hepatomegaly 15.1 13.10 3.1 31.17 21.3 19.5 — — — —Step 230: Episode Treatment Stage Rule

Identifying different treatment stages, including initial, active, andfollow-up treatment, is important in medical conditions such as thefollowing: breast cancer, prostate cancer, colorectal cancer, acutemyocardial infarction, and lymphoma.

The Grouper function is designed to separate initial, active, andfollow-up treatment episodes using key episode identification markers,or triggers, for each applicable medical condition. Then, these episodetypes are separately examined to perform physician efficiencymeasurement.

Initial, active, and follow-up treatment stages are defined using breastcancer as an example. An initial breast cancer episode is one where thepatient has a surgery for the cancer (e.g., lumpectomy, modified radialmastectomy). An active breast cancer episode is one where no surgery ispresent, but chemotherapy or radiation treatment is observed within theepisode. Here, the patient underwent surgery in a previous study period,so no surgical event is found in the patient's current ongoing breastcancer episode. Instead, during the study period, the claims data showsthat the patient is being treated with chemotherapy and/or radiation.The presence of these treatments defines an active breast cancerepisode. The utilization pattern and charges are different for an activebreast cancer patient as compared to an initial breast cancer patient. Afollow-up breast cancer episode is one where no surgery, chemotherapy,or radiation treatment is present in the patient's episode of care.After initial and active treatments, physicians will continue to codefor breast cancer over the future years of patient follow-up care.

In a given study period, physicians do not treat an equal distributionof each episode type (initial, active, and follow-up). Moreover, theepisode types have different average charges. The group functioncorrectly identifies treatment stages and examines them separately toensure that physician efficiency scores accurately reflect thephysician's practice.

Table 16 presents selected triggers descriptions and the applicableprocedural codes (CPT-4, HCPCS, and UB92) for trigger formation. Forinstance, the mastectomy trigger consists of CPT-4 codes 19120-19272,whereby a trigger event of mastectomy may be formed if one or more CLIsin a patient's episode have CPT codes 19120-19272. Table 17 lists theselected triggers as they apply to several medical conditions thatrequire treatment staging. The episode treatment stage rule accessesTable 16 and Table 17 and determines if the appropriate triggers existto classify a patient's episode as initial, active, inactive, orfollow-up.

TABLE 16 Selected Triggers for Differentiating Initial/Active/Inactive,Active/ Inactive, Initial/Follow-Up, Active/Follow-up, andInitial/Active/Follow-up Trigger HCPCS UB92 Number Trigger DescriptionCPT-4 Codes Codes Codes 5 Breast tissue expander 11960-11971 9Mastectomy 19120-19272 10 Breast repair 19316-19499 16 Bone marrowtransplant 38230-38241, 85120 17 Repair constricted aorta 33840-33855,33619 20 Lymphadenectomy 38562-38564 21 Lymph node excision 38300-3855926 Liver surgeries 47001-47136, 47380-47399 28 Exploratory laparotomy49000 39 Sterotactic brain 61720-61770 procedure 46 Emergency room visit99281-99285, 981 90500-90560 47 Inpatient visit 99221-99239, 98799251-99263, 99291-99298, 99431-99440, 90200-90292, 99160-99172 48Chemotherapy drugs J0640, J1020- J1094, J1040, J1100, J1440 J1710-J1720,J1830, J2320- J2322, J2920- J2930, J7505, J8530-J8610, Q0083 49Chemotherapy 96400-96549 280, 289, administration 335 50 Radiationtherapy 77261-77499 330-333, 342

TABLE 17 Selected Trigger Applications for Medical Conditions:Initial/Active/Inactive, Active/Inactive, Initial/Follow-Up,Active/Follow-up, and Initial/Active/Follow-up Aortic Aneurysm LymphomaMalignant neoplasm, breast Trigger Active Follow-Up Active InactiveInitial Active Follow-up Number Trigger Description 10.21 10.22 21.521.6 30.8 30.9 30.10 5 Breast tissue expander Yes 9 Mastectomy Yes 10Breast repair Yes 16 Bone marrow transplant Yes Yes 20 LymphadenectomyYes Yes 21 Lymph node excision Yes Yes 26 Liver surgeries Yes 28Exploratory laparotomy Yes 39 Sterotactic brain procedure Yes 46Emergency room visit Yes 47 Inpatient visit Yes 48 Chemotherapy drugsYes Yes 49 Chemotherapy administration Yes Yes 50 Radiation therapy YesYes

For example, a patient's malignant neoplasm of the breast episode may beclassified as initial if the following trigger events are present:breast repair, bone marrow transplant, lymphadenectomy, or lymph nodeexcision. A patient's malignant neoplasm of the breast may be classifiedas active if the following trigger events are present: breast tissueexpander, breast repair, chemotherapy drugs, chemotherapyadministration, or radiation therapy.

However, the rule also examines Table 18 to determine whether thetriggers meet specific qualifying event criteria. If a trigger eventdoes not meet one of the specified criteria in Table 18 for a medicalcondition, then the trigger event does not count. For instance, in orderfor a patient's malignant neoplasm of the breast to be classified asinitial, the table shows that: (1) one of the trigger events identifyingthe episode as initial needs to be $150 or more; or (2) two or moretrigger events need to be present in the episode.

If these criteria are not met for the episode to be assigned to theinitial treatment stage, then the rule accesses the Table 18 todetermine if the patient's episode of malignant neoplasm of the breastmay be assigned to the active treatment stage. The active treatmentstage is assigned if a specific trigger event has a claim line item(CLI) on three different days. If no specific trigger event has a CLI onthree different days, then the patient's episode is classified asfollow-up.

TABLE 18 Qualifying Event Criteria for Triggers to Apply to MedicalConditions: Initial/Active/Inactive, Active/Inactive, Initial/Follow-Up,Active/Follow-up, and Initial/Active/Follow-up Medical Condition MedicalCondition Number Long Description Criteria Examined Qualifying Event10.19 Aortic aneurysm, initial Criterion 1, or 1 trigger procedure >$150Criterion 2, or Need >2 different trigger proc Criterion 3 Any 1 triggerCLI on 3 different days 10.20 Aortic aneurysm, follow-up Episodedefaults to 10.20 if Criteria 1-3 above not achieved. 21.5 Lymphoma,active Criterion 1, or 1 trigger procedure >$150 Criterion 2, or Need >2different trigger proc Criterion 3 Any 1 trigger CLI on 3 different days21.6 Lymphoma, inactive Episode defaults to 21.6 if Criteria 1-3 abovenot achieved. 30.8 Malignant neoplam of breast, initial Critierion 1, or1 trigger procedure >$150 Criterion 2, or Need >2 different trigger procCriterion 3 Not applicable Episode defaults to 30.9 if Criteria 1-3 notachieved. 30.9 Malignant neoplasm of breast, active Rule now examines ifepisode meets following criteria: Critierion 1, or Any 1 trigger CLI on3 different days Criterion 2, or Not applicable Criterion 3 Notapplicable 30.10 Malignant neoplasm of breast, follow-up Episodedefaults to 30.10 if Criteria 1-3 above not achieved.Stage 240: Complex Condition Merge Rule

Certain medical conditions represent the combination of two or moremedical conditions in the same PMC Group. For example, diabetes mellituswith multiple complications (17.6) is one such medical condition. TheGrouper function initially formulates one or more of the followingepisodes of diabetes for a patient: 17.1 diabetes mellitus with nocomplications; 17.2 diabetes mellitus with ophthalmic manifestation;17.3 diabetes mellitus with neurologic manifestation; 17.4 diabetesmellitus with circulatory manifestation; and 17.5 diabetes mellitus withrenal manifestation.

The complex condition merge rule then examines all initially formedepisodes of diabetes for a patient and determines whether the patienthas any of the combinations listed in Table 19. For instance, if apatient has an episode of diabetes with no complications (17.1) and anepisode of diabetes with ophthalmic manifestations (17.2), then bothepisodes will be merges into 17.2. The rule also accesses the table toform diabetes with multiple complications (17.6). This medical conditiondoes not exist before the complex condition merge rule. Table 19 showsthat a patient is placed into diabetes with multiple complications(17.6) if the patient has any combination of 17.2, 17.3, 17.4, and 17.5.

The final list of diabetes medical conditions is as follows: 17.1diabetes mellitus with no complications; 17.2 diabetes mellitus withophthalmic manifestation; 17.3 diabetes mellitus with neurologicmanifestation; 17.4 diabetes mellitus with circulatory manifestation;17.5 diabetes mellitus with renal manifestation; and 17.6 diabetesmellitus with multiple complications.

TABLE 19 Complex Condition Merge for Diabetes Mellitus Medical MedicalPatients Episodes are Merged Condition Condition And Placed into HighestNumber 1 Number 2 Resource Intensity Episode 17.1 17.2 17.2 17.1 17.317.3 17.1 17.4 17.4 17.1 17.5 17.5 — Any combination 17.6 of 17.2, 17.3,17.4 and 17.5Step 250: Complication Episode Merge Rule

The Grouper function uses the complication episode merge rule toidentify medical conditions as complicating factors to a patient'sunderlying medical condition being examined. Complicating factors arepatient-specific episodes that are clinically determined to be relatedto the underlying disease.

For example, physicians' code up to 70% of an average diabetic's chargesunder the related complications to diabetes (e.g., neuropathies,circulatory, eye, renal) and not diabetes care. This is becausephysicians frequently code only for the specific condition that they aretreating at the time, which is often not diabetes. Therefore, withoutconsidering and including complication episodes with the actual diabetesepisode, patient severity-of-illness and physician efficiencydifferences may be attributed to incomplete episode charges andutilization.

Another example is human immunodeficiency virus (HIV) conditions wheretracking related complications is important or up to 80% of an averageHIV patient's charges and utilization may be under-reported. Thesecomplicating conditions include pneumonia, opportunistic infections(e.g., cryptococcosis, candidiasis), nerve conditions, eye conditions,blood disorders, and malignancies. The Grouper function includes relatedcomplications and links them to the underlying condition being examined.

A third example is maternity conditions where complications before birthand complications of delivery are important to track to single andmultiple newborn deliveries. Otherwise, up to 50% of an averagematernity patient's charges and utilization may be under-reported.

Using HIV conditions as an example for applying the complication episodemerge rule, the Grouper function initially formulates the followingunderlying medical condition episode for a patient: 3.1 Asymptomatic HIVinfection.

One or more medical conditions then are linked as complications to theunderlying medical condition of asymptomatic HIV infection. This linkagemay result in the underlying medical condition episode being upcoded toa more resource intensive medical condition to reflect the physiologicprogression of the disease and/or the underlying medical conditionepisode being moved to a higher severity-of-illness (SOI) class.

Table 20 shows the medical conditions linked to asymptomatic HIVinfection (3.1) that will upcode the patient's episode to HIV withinfectious complication (3.2). The rule accesses Table 20 to determineif any of the complication medical conditions are present for thepatient. If yes, then the patient is upcoded to HIV with infectiouscomplication (3.2). For all complication episodes, the charges andutilization are merged into the ongoing HIV with infectious complicationepisode.

TABLE 20 Complication Medical Conditions Linked to the UnderlyingMedical Condition of HIV Infection Medical Complication HIV with InfectComp (3.2) Cond Condition Complication Condition SOI SOI SOI NumberVerbal Description Number Verbal Description Class Class Class 3.2 HIVwith infectious comp 2.5 Tuberculosis 1 2.5 Tuberculosis 2 2.5Tuberculosis 3 2.11 Cytomegalic inclusion dz 1 2.16 Cryptococcosis 12.17 Candidiasis 1 2.17 Candidiasis 2 2.17 Candidiasis 3 2.18Coccidioidomycosis 1 2.18 Coccidioidomycosis 2 2.18 Coccidioidomycosis 32.19 Histoplasmosis 1 2.19 Histoplasmosis 2 2.19 Histoplasmosis 3 2.20Blastomycotic infection 1 2.20 Blastomycotic infection 2 2.23Toxoplasmosis 1 2.23 Toxoplasmosis 2 2.23 Toxoplasmosis 3 2.24Pneumocystosis 1 9.7 Pneumonia 1 9.7 Pneumonia 2 9.7 Pneumonia 3

The rule then examines the SOI class of the linked complication medicalcondition episode. For instance, Table 20 illustrates that toxoplasmosisepisodes with SOI-1 rank will not move the patient's HIV with infectiouscomplication episode to a higher SOI class. However, the table showsthat toxoplasmosis episodes with SOI-2 rank will move the patient's HIVwith infectious complication episode to the SOI-2 class.

After applying the complication episode merge rule, Table 21 shows thata patient with HIV infection may be placed into one of the following PMCGroup 3 medical conditions and SOI classes.

TABLE 21 Human Immunodeficiency Infection Medical Conditionsand SOIClasses After Linking of Complication Episodes Medical Number ofCondition Medical Condition Severity Number Long Description Classes 3Human Immunodeficiency Infections 3.1 HIV infection with nocomplications 1 3.2 HIV infection with infectious complication 3 3.3 HIVinfection with CNS involvement 3 3.4 HIV infection with malignancy 3 3.5HIV infection with multiple complications 3Step 260: Comorbidity Marker Rule

In an embodiment, the Grouper function also uses a comorbidity markerrule to identify medical conditions as comorbidities to a patient'smedical condition being examined. A comorbidity is a concurrentresource-intensive medical condition that is not related to theunderlying disease state. For example, breast cancer is considered acomorbid condition to diabetes.

With respect to comorbidities, the individual physician efficiencyanalysis may eliminate from analysis any patient episode with a linkedcomorbidity. If such episodes are not eliminated, unnecessaryheterogeneity may remain within condition-specific episodes. Thisheterogeneity adds error to any evaluation of physician efficiency.

Table 22 presents selected comorbid medical conditions. As indicated inTable 22, for a comorbid medical condition to be tracked to a medicalcondition episode in question, the patient's comorbid medical conditionepisode needs to be of a certain SOI class and total charge amount. Forexample, Table 22 shows that a patient's seizure disorder needs to be ofSOI-2 class and at least $2,500 to be linked to another medicalcondition as a comorbidity. It is to be understood that the medicalconditions listed in Table 22 do not need to have qualifying events,such as a charge amount or SOI level.

TABLE 22 Selected List of Medical Condition Comorbiditiesto a Patient'sMedical Condition Being Examined Mini- Mini- Medical mum mum ConditionMedical Condition Episode SOI Number Long Description Charges Level 2.4Septicemia $3,500 1 2.5 Tuberculosis $2,500 1 2.11 Cytomegalic inclusiondisease $3,500 1 3.4 HIV infection with malignancy $1,500 1 3.5 HIVinfection with multiple $1,500 1 complications 4.11 Inflammatorydiseases of CNS $3,500 1 4.19 Multiple sclerosis $2,500 1 4.24 Malignantneoplasm of brain, initial care $2,000 1 4.25 Malignant neoplasm ofbrain, active care $2,000 1 9.13 Emphysema $3,000 2 9.14 Chronicobstructive pulmonary disease $4,000 1 9.15 Spontaneous pneumothorax$2,500 1 9.19 Malignant neoplasm of bronchus and $3,000 1 lung, active10.16 Congestive heart failure $3,000 2 10.17 Cardiomyopathy $3,000 210.21 Acute myocardial infarction, active $3,500 1 10.22 Acutemyocardial infarction, follow-up $3,000 1 11.14 Cerebrovascularhemorrhage $2,500 1 13.20 Crohn's disease $3,000 2 13.27 Malignantneoplasm of stomach $2,000 1 13.30 Malignant neoplasm of colon, initial$3,500 1 15.10 Chronic liver disease $2,500 2 15.11 Liver transplant$2,000 1 15.14 Malignant neoplasm of pancreas $2,000 1 17.5 Diabetesmellitus with renal $3,750 1 manifestation 17.6 Diabetes mellitus withmultiple $3,750 1 complications 20.9 Malignant neoplasm of spleen $2,0001 29.27 Kaposi's sarcoma $2,000 1 31.19 Rheumatoid arthritis $3,000 234.31 Organic dementias $3,000 2 34.32 Schizophrenia $3,000 2Step 270: Partial Episode Marker Rules

The Gouper function determines partial and complete episodes of care forboth acute and chronic episodes. The user decides whether to include orexclude partial episodes of care from analysis using the parameterSWITCH_DROPPARTIAL in the RUN.INI file (refer to Table 6).

In an embodiment, the system of the present invention uses differentanalytical approaches to identify partial episodes for acute and chronicmedical conditions, as described below.

With respect to acute conditions, the partial episode marker rule statesthat acute episodes must pass the tests defined in Table 23 for both thebeginning and the end of the study period, or the episodes will bemarked as partial. The maximum allowable duration for any acutecondition is 180 days.

TABLE 23 Partial Acute Episodes of Care If the medical condition windowperiod is: Then the episode is marked as partial when it: Study-StartPartial Episodes (Episodes declared partial because they may have begunbefore the start of the study period.) Equal to or greater than 90 daysBegins within 30 days of the start of the study period Less than 90 daysBegins closer than 33% of the window period from the start of the studyperiod Study-End Partial Episodes (Episodes declared partial becausethey may not be complete at the end of the study period.) Equal to orgreater than 120 days Begins during the last quarter of the study periodLess than 120 days The last CLI associated with the episode is closerthan 33% of the window period to the end of the study period, unless theepisode has been under way for 180 days

For acute conditions having a window period equal to or greater than 120days, the last three months of the study period are used as a run-outinterval to allow all incomplete acute episodes as of the beginning ofthe fourth quarter to end. Allowing for a run-out interval reduces thefragmentation of acute episodes and therefore increases the validity andreliability of treatment pattern results.

For acute conditions having a window period less than 120 days, theepisode will be marked as partial if the last CLI associated with theepisode is closer than 33% of the window period to the end of the studyperiod. For example, upper respiratory infection (URI) has a windowperiod of 60 days. Assume a patient's ongoing episode of URI has a CLIwith a date of service of December 20, and the end of the study periodis December 31. Then, this URI episode would be marked as partialbecause the episode's last CLI is less than 33% of the window period (or20 days) to the end of the study period.

In an embodiment, all chronic medical condition episodes begin duringthe first half of the study period to be considered complete episodes ofcare. Chronic episodes beginning in the second half of the study periodare treated as partial. In an embodiment, the duration for a chroniccondition is 180 days for the physician efficiency analysis. However,chronic conditions may continue on indefinitely as recognized by thewindow period of 365 days (refer to Table 11 for chronic disease windowperiods of 365 days).

Step 6: Perform PATAN Output Process

The PATAN output process involves four main functions.

The first function is to eliminate episodes of care that have beenmarked for removal during the read in RUN.INI file step. These episodesinclude: (1) partial episodes of care; and (2) episodes marked withcomorbidities. If these two types of episodes have not been marked fordeletion, then the episodes will be presented in the PATAN output file.

The second function is to assign episodes to physicians using theepisode assignment logic as defined by the parameterSWITCH_ASSIGNTHRESHOLD during the read RUN.INI file step. Generally, theuser is interested in examining those episodes of care where thephysician recommends treatment and follow-up services. Therefore, anassignment rule is included that allows the physician to be a keytreatment provider, but also allows for the physician to refer toanother specialist for ongoing treatment. This assignment rule specifiesthat when a physician incurs a given percent of charges in an episode ofcare, that episode is assigned to that physician.

For the physician efficiency analysis, an assignment value of 20%usually is employed, but the user can change the assignment rule from1-100% using the parameter SWITCH_ASSIGNTHRESHOLD in the RUN.INI file(refer to Table 6).

Using this rule, all professional charges are added in each episode ofcare, including office visits, lab/path services, medical and surgicalprocedures, and diagnostic tests. These professional charges may occuron an office visit, clinic, hospital outpatient, hospital inpatient, orother professional setting basis (e.g., nursing home, halfway home, homevisit professional charges). All facility charges and prescription drugsare excluded. However, in an embodiment, other services may be includedfrom an episode of care for the physician assignment rule.

For example, consider an assignment rule equal to 20%. This means thatwhen a physician has 20% or more of all professional charges, theepisode is assigned to that physician. At the 20% level, this rulegenerally results in episodes being assigned to about 1.20 physicians(or up to 20% of episodes may be assigned to more than one physician).Chronic disease episodes (e.g., asthma) are assigned to more than onephysician more often than acute episodes (e.g., acute bronchitis).

When an episode is not assigned to any physician using the 20%assignment rule, another rule is employed which assigns that episode tothe physician who has the highest percent of professional charges withinthe episode. For example, using the 20% assignment rule, if no physicianhas 20% or more of the professional charges, and the physician who comesclosest to meeting this rule has 17% of professional charges in theepisode of interest, then the episode is assigned to this physician andno other.

The third function of the PATAN output process is to group CLIs inepisodes into 11 major service categories and 21 sub-service categories.During the extract core claims data fields step, a BETOS code isassigned to each service on a CLI (e.g., CPT-4, HCPCS). The BETOS codeassignment allows for CLIs to be grouped into one of 11 major servicecategories and 21 sub-service categories. Table 24 presents the type ofservice codes that match to each BETOS code. Then, the type of servicecodes are mapped to the 11 major service and 21 sub-service categories.Service and sub-service categories are formed during the PATAN outputprocess.

TABLE 24 Type of Service Codes and BETOS Codes Type Of Service Code Usedfor Service Type of Service Processing Category Code BETOS Code 0 OtherMedical Unknown — Services 1 Professional Office Visit M1x Visits 2Professional Hospital Visit M2x Visits 3 Professional ER Visit M3 Visits4 Professional Other Visit M4x, M5x, M6 Visits 5 Other MedicalAnesthesia P0 Services 6 Med/Surg Procedure P1x, P2x, P3x, ProceduresP4x, Pyx, P6x 7 Other Medical Radiation Therapy P7A Services 8 OtherMedical Other Oncology P7B Services 9 Med/Surg Endoscopy P8x Procedures10 Other Medical Dialysis Service P9x Services 11 Diagnostic Imaging 1xxTests 12 Other Medical Venipuncture T1A Services 13 Lab/Path Lab TestT1B, T1C, T1D, T1E, T1F, T1G, T1H 14 Diagnostic Functional Tests T2xTests 15 Other Medical Durable Medical Dxx Services Equipment/Supplies16 Other Medical Ambulance O1A Services 17 Other Medical ChiropracticO1B Services 18 Other Medical Enteral/Parenteral O1C Services 19 OtherMedical Chemotherapy O1D Services 20 Other Medical Other Drugs O1EServices 21 Other Medical Vision/hearing/speech O1F Services Services 22Other Medical Immunization O1G Services 23 Other Medical Other NECServices Y1, Y2, Z1, Z2 Services

The fourth function of the PATAN output process is to implement themaximum duration rule for episodes of care, which is 180 days.

For chronic conditions (e.g., diabetes, asthma, ischemic heart disease),an episode of care begins when a CLI is initially found during the studyperiod that has a defined ICD.9 code that has been assigned to thatmedical condition. Then, chronic conditions may continue on indefinitelyas recognized by the window period of 365 days. However, for thepurposes of physician efficiency analysis, chronic conditions areconsidered to have a 180-day duration. Therefore, a chronic conditionends 180 days after identifying the first CLI with a diagnosis (definedICD.9 code) for the specific chronic condition. The rule determines thatthe patient is present for 180 days during the study period after thefirst CLI with a diagnosis for the specific chronic condition.

For acute conditions (e.g., upper respiratory infections, otitis media,conjunctivitis), the maximum allowable duration for the physicianefficiency analysis also is 180 days. The embodiment recognizes thatthis maximum allowable duration may be varied.

Step 7: Store PATAN Output File

The PATAN Output File is stored in episode of care identifier order(Field 1 in Table 25). Table 25 lists the fields present on the PATANOutput File.

TABLE 25 Fields in the PATAN Output File Field Field Descriptive NumberName Notes (Section A) Non-Repeated Episode Fields 1 Episode ID Theunique episode ID for each medical condition treatment episode. 2Medical ConditionThe medical condition internal ID number. Number 3 SOISeverity of Illness index, where 1 is the least severe and 3 is the mostsevere or difficult to treat as defined for the medical condition. 4Episode Duration The duration of the medical condition treatmentepisode, in days. 5 Total Episode The total allowed charges for thetreatment episode, in dollars. Charges 6 Professional Total allowedcharges claimed by professional (excludes Rx and facility) Chargesphysicians. 7 Physician ID Identifies each physician that hadsignificant involvement in the treatment for the episode. If multiplephysicians were significantly involved in treating the episode, multiplerows are output for the episode, one for each physician. 8 PhysicianSpecialty Identifies the specialty number associated with the physician.Since the specialty is determined by the PROVSPEC module, this fieldcontains the value 0 in the version of the output from PATAN. 9Physician Identifies the marketbasket number associated with thephysician. Since Marketbasket the marketbasket is determined by thePROVSPEC module, this field contains the value 0 in the version of theoutput from PATAN. 10 Physician Identifies the aggregate grouping numberassociated with the physician. Aggregate Since the aggregate groupingnumber is determined by the PROVSPEC Grouping Code module, this fieldcontains the value 0 in the version of the output from Number PATAN. 11[not valid for This field is not valid for the commercial population.Always contains the commercial value 1. population] 12 Physician ChargesThe is the charge component amount of the Professional Charges field(see above referenced field) that is attributable to the physicianidentified by the Physician ID field (see above referenced field). 13Patient Age The age of the patient at the beginning of the study period.(Section B) Repeated Episode Fields for Each Service Category (11 timesper row) 1 Service Category Eleven fields that contain utilization dataat the service category level. Utilization 2 Service Category Elevenfields, ten of which contain charges in dollars at the service Chargescategory level (field 9 is not used because the system of the presentinvention does not break out charge data for inpatient admits). (SectionC) Repeated Episode Fields for Each Sub-Service Category (21 times perrow) 1 Sub-Service Twenty-one fields that contain utilization data atthe sub-service category Category Utilization level. 2 Sub-ServiceTwenty-one fields, twenty of which contain charges in dollars at thesub- Category Charges service category level (field 14 is not usedbecause the system of the present invention does not break out chargedata for inpatient admits).Step 8: Sort PATAN Output File by Provider ID: PROVSORT1

The PATAN Output File is sorted by the primary sort key of physicianidentifier. The secondary sort key is the episodes assigned to aphysician.

Step 9: Read in Episode Assignments from PROVSORT1

The episode assignments by physician from PROVSORT1 are read into thephysician specialty module (PROVSPEC). PROVSPEC completes several of themissing fields in the PATAN Output File (refer to Table 25): (1)physician specialty (Field 8); (2) physician marketbasket (Field 9); and(3) physician aggregate grouping code number (Field 10).

Step 10: Assign Specialty Type to Physician

The PROVSPEC module employs a rule to select the most appropriatephysician specialty when a physician has more than one specialty typeassigned in the physician provider file. This processing step is helpfulin selecting a specialty type that is most reflective of the physician'sactual practice during the study period.

The rule examines all episodes associated with a physician and assignseach episode to one of the 31 marketbasket specialty types (refer toTable 26). A marketbasket consists of the most common conditions treatedby each physician specialty type. The term physician is used broadly,and includes other professionals delivering medical care services, suchas chiropractors, acupuncturists, podiatrists, nurse practitioners, andphysical therapists.

Medical conditions are tracked to a specialty-specific marketbasket ifthey generally account for 60% to 80% of the episodes treated by thatspecialist type. The medical conditions are selected for themarketbasket in work effort order, which is a function of the prevalencerate of a condition and the average charges to treat a patient's episodeof care. The embodiment recognizes that additional marketbaskets may bedeveloped for other specialty types.

Several examples of medical conditions in special-specific marketbasketsare as follows. Hypertension, low back pain, and sinusitis are withinthe general internist marketbasket. Otitis media, upper respiratoryinfections, sinusitis, and rhinitis are within the pediatricmarketbasket. Obstetrics/gynecology: single newborn normal delivery,cervicitis, and endometriosis are within the obstetrics/gynecologymarketbasket. External abdominal hernias, cholilithiasis, and cysticbreast disease are within the general surgeon marketbasket.

The composition of medical conditions in each specialty-specificmarketbasket does not (generally) change over time. This means that anytrend increase reflected by the specialty-specific marketbasket isindependent of changes in patient demographics and health status.Instead, the trend reflects price increases, volume increases, andintensity of service increases in the treatment of the static set ofmedical conditions.

The physician specialty assignment rule eliminates any specialty typesnot already assigned to the physician in the physician provider file.The rule then looks for the marketbaskets with the most episodes amongthose remaining. For example, consider a physician who has beenidentified in the physician provider file as a general internist and acardiologist. During analysis, the rule finds the following marketbasketspecialty types associated with the physician's episodes: 37% ofepisodes are associated with Marketbasket 10, gastroenterology; 34% withMarketbasket 2, general internists; and 29% with Marketbasket 4,cardiology.

Even though 37% of the physician's episodes have been identified asgastroenterology, the physician cannot be assigned to thegastroenterology marketbasket because gastroenterology was not includedas a specialty type in the physician provider file.

The physician is observed to have more episodes in the generalinternists marketbasket than in the cardiology marketbasket. Thus, thisphysician might be assigned for efficiency analysis into the generalinternists marketbasket. However, a second rule is now applied beforeassigning this physician as a general internist and running the generalinternists marketbasket. The second rule states that if a physician hasan assigned primary care physician (PCP) designation (i.e.,family/general practitioner, general internist, or pediatrician), butalso an assigned non-PCP specialty type, then the PCP designation isignored and the physician is assigned to the specialty that has the nextmost episodes that is not a PCP designation. If another specialty typeis not present, then the physician is assigned the PCP designation offamily/general practitioner, general internist, or pediatrician asdefined in the physician provider file.

Using this rule, the physician would be placed in Marketbasket 4,cardiology, because general internist is defined as a PCP. Therefore,the rules assign the physician for efficiency analysis as acardiologist.

TABLE 26 Marketbasket Specialty Types Market- Basket Number MarketbasketSpecialty Type 1 Family and General Physicians 2 General Internists 3Allergy 4 Cardiology 5 Cardiothoracic Surgery 6 Chiropractic 7Dermatology 8 Emergency Medicine 9 Endocrinology 10 Gastroenterology 11General Surgery 12 Nephrology 13 Neurology 14 Neurosurgery 15Obstetrics/Gynecology (OB/GYN) 16 Oncology/Hematology 17 Ophthalmology18 Oral Maxillary 19 Orthopedics 20 Otolaryngology (ENT) 21 Pediatrics22 Plastic Surgery 23 Podiatry 24 Psychiatry 25 Psychology 26Pulmonology 27 Rheumatology 28 Sports/Physical Medicine 29 Urology 30Vascular Surgery 31 Critical Care (Intensivist)Step 11: Assign Physician to Marketbasket Based on Specialty Type

After the physician has been assigned to a specialty type, the physicianis then assigned to a marketbasket. The physician specialty codes inTable 3 are mapped to the marketbasket specialty types in Table 26. BothTable 3 and Table 26 are accessed to assign physicians to amarketbasket.

Step 12: Assign Physician to Report Group

Report group structures are important because they allow the formationof peer groups to which physicians can be compared. PROVSPEC provides atool to build report group structures that interest the user. The toolprovides flexibility in building report groups reflecting comparisonsthat are relevant to the user. Example report groups include geographicregions, physician groups, and benefit plan designs.

The basis for creating report groups is the Detailed Grouping Code(refer to Table 1, Field 35). A Detailed Grouping Code is aclient-specified identifier that is the base data element aggregated toform a report group. For example, zip codes or tax identificationnumbers can be Detailed Grouping Codes.

An Aggregate Grouping Code represents a group of Detailed Grouping Codes(refer to Table 25, Section A, Field 10). The Aggregate Grouping Code isa number the user chooses. The output of the system of the presentinvention contains information organized by Aggregate Grouping Code.Therefore, the aggregate groups the user develops are the foundation forreport group structures contained in output files and printed reports.

The process of developing a report group structure is a now described.First, the user decides on a grouping structure. When formulating agrouping structure, the user needs to consider the nature of thecomparison. For example, one comparison may be geographic comparisonsbased on zip code of physician place of service. The grouping structureshould assure that each group has a large enough member base to makecomparisons meaningful.

Second, an Aggregate Grouping Code is assigned to each group that hasbeen defined. The code is a positive integer that has been selected. Itis used by the system of the present invention to represent the groups.For example, when comparing on the basis of geographic regions, eachAggregate Grouping Code might represent a specific region that has beendefined by identifying individual zip codes.

Detail codes are then determined based on the comparison to be made. Forexample, for geographic comparisons, the detail codes might be physicianoffice address zip codes.

Each Detailed Grouping Code is then assigned to an Aggregate GroupingCode. The user does this by creating a simple two-column table in whichthe first column is the Detailed Grouping Code and the second column isthe Aggregate Grouping Code. The task is accomplished by developing aspreadsheet for relatively small groups or with a database program forlarger groups.

The grouping map is then saved as a file, and referenced in the RUN.INIFile. The user may name the file as desired, and the user needs to editthe RUN.INI File so that it includes the correct file name. Output filesand reports are organized using the report group structure that has beendefined.

A geographic region analysis might use physician office zip codes as thebasis for forming groups. The user would employ the following process tobuild the report group structure: identify the geographic regions ofinterest; assign each region an arbitrary code number; each physicianmust then be identified as belonging to a region; and assign or mapphysician office zip codes to the code numbers representing geographicregions. Table 27 shows how the user can map zip codes to regions.

TABLE 27 Grouping by Geographic Region Detailed Grouping Code AggregateGrouping Code Physician's office Zip Code Code number representing aclient- defined geographic region

A physician group analysis might use physician identification numbers asthe basis for forming groups. In this embodiment, the user employs thefollowing process to build the report group structure: identify thephysician groups of interest; assign each physician group an arbitrarycode number; identify each physician as belonging to a group; and assignor map physician identification numbers to the code numbers representingphysician groups. Table 28 shows how the user would map physicianidentification numbers to the code numbers representing physiciangroups.

TABLE 28 Grouping by Physician Group Detailed Grouping Code AggregateGrouping Code Physician ID Number representing a physician groupStep 13: Determine Eligible Physicians and Episode Assignments

This step involves three main functions. The first function is to filteror eliminate physicians with an assigned specialty type that cannot beassigned to one of the 31 marketbaskets. For example, there is noradiologist marketbasket, so radiologists would be removed by this rule.

The second function is to eliminate physicians that are not in a reportgroup of interest. This rule examines the physician's assigned DetailedGrouping Code as compared to the Aggregate Grouping Codes of Interest.If the Detailed Grouping Code does not match to an Aggregate GroupingCode of interest for an established RUN.INI File run, then the physicianis filtered out from further analysis.

The third function is to filter out episode assignments not in amarketbasket. For physicians in a Report Group of interest for anestablished RUN.INI File run, episode assignment rows in the PROVSORT1input file that are not relevant to the marketbasket in which thephysician will be profiled are filtered by PROVSPEC processing. ThisPROVSPEC rule checks to ensure that the medical conditions treated bythe physician are included in the FILE_MBCONDITIONS File for thephysician's marketbasket (refer to Table 6, Parameters in the RUN.INIFile). Medical conditions that are not in the physician's marketbasketare removed from analysis.

Another PROVSPEC rule checks to ensure that the age of the patient fallswithin the age range specified in the FILE_SPECAGE File for a definedmarketbasket (refer to Table 6, Parameters in the RUN.INI File). If not,that patient's episode of care is removed from analysis. The user canmodify the FILE_SPECAGE File.

With respect to the FILE_MBCONDITIONS File, both commercial and Medicaremarketbaskets have been defined. There are a total of 31 commercialmarketbaskets by physician specialty type. Commercial means a populationof individuals under 65 years of age that are not eligible to receiveMedicare benefits. There are a total of 31 Medicare marketbaskets byphysician specialty type. Medicare means a population of individuals 65years of age and older that are eligible to receive Medicare benefits.

Each medical condition in a specialty-specific marketbasket is assigneda weight factor that reflects the importance or relevance of thatmedical condition to the marketbasket. However, in an embodiment, no onemedical condition receives more than a 30% weight factor to prevent aphysician's treatment pattern for that condition from dominating theresults of a marketbasket.

The weight factors are used to compute the overall marketbasket weightedaverage value of a charge or utilization service category—across medicalconditions—for a peer group or a physician. The sum of the weightfactors in a marketbasket equals 1.00.

Therefore, regardless of a physician's (or peer group's) actual episodework effort, the rule standardizes each physician's actual work effortto a static set of weight factors. These weight factors represent thework effort that an average specialty-specific physician treats inmedical practice, where work effort is a function of the prevalence rateand the average charges to treat an episode of care. This standardizedweighting allows for an apples-to-apples comparison of one physician'smarketbasket results to another physician's marketbasket results.

Tables 29-60 present the 31 commercial marketbaskets listed in Table 26,Marketbasket Specialty Types. The last column in each marketbasket tablepresents the weight factor for each medical condition. It is to beunderstood that the medical conditions and severity-of-illness levelsmay change for a marketbasket.

TABLE 29 1. FAMILY AND GENERAL PRACTITIONERS Medical Market- OrderCondition SOI Medical Condition basket Number Number Level ShortDescription Weight 1 10.2 1 Hypertension 0.100 2 31.9 1 Low back pain0.050 3 31.8 1 Cervical spine pain 0.025 4 31.4 1 Bursitis 0.050 5 33.151 Degenerative joint disease 0.025 6 17.1 1 Diabetes w/no complications0.050 7 7.2 1 Sinusitis 0.050 8 7.1 1 Rhinitis 0.050 9 9.4 1 Acutebronchitis 0.050 10 9.1 1 Upper respiratory infections 0.050 11 9.7 1Pneumonia 0.050 12 13.13 1 Noninfect gastroent & colitis 0.050 13 9.11 1Asthma 0.025 14 10.13 1 Ischemic heart disease 0.025 15 36.19 1 Chestpain 0.025 16 13.6 1 Gastroesophageal reflux 0.025 17 13.5 1 Gastritisand duodenitis 0.025 18 19.4 1 Disorders of lipid metabolism 0.025 1916.3 1 Hypothyroidism 0.025 20 22.3 1 Urinary tract infections 0.025 2134.17 1 Nonpsychotic depression 0.025 22 34.14 1 Personality & disturbdsdr 0.025 23 29.9 1 Dermatitis and eczema 0.025 24 4.3 1 Headaches0.020 25 31.3 1 Other arthropathy disorders 0.020 26 20.4 1 Anemiadisorders 0.020 27 36.17 1 Abdominal pain 0.020 28 29.6 1 Skin keratoses0.015 29 29.1 1 III-defined integument sym 0.015 30 36.15 1 Generalpresenting symptoms 0.015 1.000

TABLE 30 2. GENERAL INTERNISTS Medical Market- Order Condition SOIMedical Condition basket Number Number Level Short Description Weight 110.2 1 Hypertension 0.100 2 31.9 1 Low back pain 0.050 3 31.8 1 Cervicalspine pain 0.025 4 31.4 1 Bursitis 0.050 5 33.15 1 Degenerative jointdisease 0.025 6 17.1 1 Diabetes w/no complications 0.050 7 7.2 1Sinusitis 0.050 8 7.1 1 Rhinitis 0.050 9 9.4 1 Acute bronchitis 0.050 109.1 1 Upper respiratory infections 0.050 11 9.7 1 Pneumonia 0.050 1213.13 1 Noninfect gastroent & colitis 0.050 13 9.11 1 Asthma 0.025 1410.13 1 Ischemic heart disease 0.025 15 36.19 1 Chest pain 0.025 16 13.61 Gastroesophageal reflux 0.025 17 13.5 1 Gastritis and duodenitis 0.02518 19.4 1 Disorders of lipid metabolism 0.025 19 16.3 1 Hypothyroidism0.025 20 22.3 1 Urinary tract infections 0.025 21 34.17 1 Nonpsychoticdepression 0.025 22 34.14 1 Personality & disturb dsdr 0.025 23 29.9 1Dermatitis and eczema 0.025 24 4.3 1 Headaches 0.020 25 31.3 1 Otherarthropathy disorders 0.020 26 20.4 1 Anemia disorders 0.020 27 36.17 1Abdominal pain 0.020 28 29.6 1 Skin keratoses 0.015 29 29.1 1III-defined integument sym 0.015 30 36.15 1 General presenting symptoms0.015 1.000

TABLE 31 3. ALLERGY Medical Market- Order Condition SOI MedicalCondition basket Number Number Level Short Description Weight 1 7.1 1Rhinitis 0.175 2 7.2 1 Sinusitis 0.150 3 9.11 1 Asthma 0.150 4 9.1 1Upper respiratory infections 0.075 5 9.2 1 Dz upper respiratory tract0.050 6 9.10 1 Chronic bronchitis 0.050 7 9.4 1 Acute bronchitis 0.050 87.4 1 Deviated nasal septum 0.050 9 9.3 1 Lower respiratory diseases0.050 10 29.8 1 Urticaria 0.050 11 36.12 1 Toxic effects of substances0.050 12 29.9 1 Dermatitis and eczema 0.025 13 5.2 1 Conjunctivitis0.025 14 6.5 1 Otitis media 0.025 15 9.5 1 Hypertrophy tonsils & aden0.025 1.000

TABLE 32 4. CARDIOLOGY Medical Market- Order Condition SOI MedicalCondition basket Number Number Level Short Description Weight 1 10.13 1Ischemic heart disease 0.150 2 10.13 2 Ischemic heart disease 0.050 317.4 1 Diabetes with circulatory 0.050 4 17.4 2 Diabetes withcirculatory 0.050 5 10.21 1 Acute myocardial infrct, active 0.075 610.22 1 Acute myocardial infrct, fup 0.025 7 10.2 1 Hypertension 0.075 810.5 1 Supraventricular arrhythmias 0.050 9 10.4 1 Ventriculararrhythmias 0.050 10 10.1 1 Abnormal heart beat 0.050 11 10.14 1 Heartvalue disorders 0.050 12 36.19 1 Chest pain 0.050 13 10.10 1 Conductiondisorders 0.050 14 10.16 1 Congestive heart failure 0.050 15 10.17 1Cardiomyopathy 0.050 16 19.4 1 Disorders of lipid metabolism 0.025 1710.11 1 Other heart disease 0.025 18 10.8 1 Angina pectoris 0.025 1910.12 1 Rheumatic heart disease 0.025 20 36.18 1 Dyspnea 0.025 1.000

TABLE 33 5. CARDIOTHORACIC SURGERY Medical Market- Order Condition SOIMedical Condition basket Number Number Level Short Description Weight 110.13 1 Ischemic heart disease 0.175 2 10.13 2 Ischemic heart disease0.025 3 10.21 1 Acute myocardial infrct, active 0.100 4 10.22 1 Acutemyocardial infrct, fup 0.025 5 17.4 1 Diabetes with circulatory 0.050 617.4 2 Diabetes with circulatory 0.025 7 9.12 1 Benign neop bronchus &lung 0.050 8 9.19 1 Malig neop bron/lung, active 0.050 9 11.8 1Generalized arteriosclerosis 0.050 10 12.5 1 Varicose veins lower extrem0.050 11 9.9 1 Pleurisy 0.050 12 9.15 1 Spon pneumothorax 0.050 13 10.121 Rheumatic heart disease 0.050 14 10.10 1 Conduction disorders 0.025 1510.14 1 Heart value disorders 0.025 16 10.19 1 Aortic aneurysm, initial0.025 17 10.20 1 Aortic aneurysm, fup 0.025 18 10.16 1 Congestive heartfailure 0.025 19 10.17 1 Cardiomyopathy 0.025 20 11.7 1 Disorders ofarteries 0.025 21 15.4 1 Cholelithiasis 0.025 22 30.2 1 Cystic breastdisease 0.025 23 11.12 1 Occlusion of cerebral arteries 0.025 1.000

TABLE 34 6. CHIROPRACTIC Medical Market- Order Condition SOI MedicalCondition basket Number Number Level Short Description Weight 1 31.9 1Low back pain 0.225 2 31.9 2 Low back pain 0.075 3 31.6 1 Nonallopathiclesions 0.150 4 31.6 2 Nonallopathic lesions 0.050 5 31.8 1 Cervicalspine pain 0.150 6 31.8 2 Cervical spine pain 0.050 7 31.3 1 Otherarthropathy disorders 0.100 8 4.7 1 Nerve root and plexus dsdr 0.050 931.13 1 Minor injury of trunk 0.050 10 31.12 1 Scoliosis 0.025 11 33.151 Degenerative joint disease 0.025 12 31.4 1 Bursitis 0.025 13 4.1 1Neuritis upper, lower limbs 0.025 1.000

TABLE 35 7. DERMATOLOGY Medical Market- Order Condition SOI MedicalCondition basket Number Number Level Short Description Weight 1 29.17 1Acne 0.125 2 29.19 1 Benign neoplasm of skin 0.075 3 29.9 1 Dermatitisand eczema 0.075 4 29.23 1 Psoriasis and pityriasis 0.075 5 29.26 1Other malignancy of skin 0.075 6 29.14 1 Dermatophytoses 0.050 7 2.9 1Viral warts 0.050 8 29.6 1 Skin keratoses 0.050 9 29.13 1 Rosacea 0.05010 30.1 1 Inflammatory disease of breast 0.050 11 29.21 1 Dz of hair andhair follicles 0.050 12 29.5 1 Other dsdr skin/subcutan tiss 0.025 1329.15 1 Sebaceous cyst 0.025 14 29.24 1 Carcinoma in situ of skin 0.02515 29.8 1 Urticaria 0.025 16 29.22 1 Erythematous condition 0.025 1721.2 1 Hemangioma 0.025 18 29.10 1 Cellul & abscess, finger/toe 0.025 192.8 1 Herpes simplex 0.025 20 29.28 1 Malig melanoma of skin, initial0.025 21 29.20 1 Dz of nail, excluding infections 0.025 22 11.1 1Pigmented nevus 0.025 1.000

TABLE 36 8. EMERGENCY MEDICINE Medical Market- Order Condition SOIMedical Condition basket Number Number Level Short Description Weight 132.5 1 Open wound hand & fingers 0.075 2 8.5 1 Open wound face & mouth0.075 3 36.19 1 Chest pain 0.050 4 11.3 1 Contusion of head and neck0.050 5 11.5 1 Cerebral laceration 0.025 6 11.4 1 Concussion 0.025 732.13 1 Fracture of radius and ulna 0.050 8 32.11 1 Fracture of handbones 0.050 9 32.1 1 Contusion of upper limb 0.050 10 33.2 1Sprain/strain of foot and ankle 0.050 11 33.1 1 Contusion of lower limb0.050 12 33.6 1 Open wound of leg 0.050 13 33.22 1 Derangement of knee0.025 14 13.13 1 Noninfect gastroent & colitis 0.050 15 9.1 1 Upperrespiratory infections 0.050 16 9.4 1 Acute bronchitis 0.025 17 36.17 1Abdominal pain 0.025 18 31.9 1 Low back pain 0.025 19 31.8 1 Cervicalspine pain 0.025 20 31.4 1 Bursitis 0.025 21 10.22 1 Acute myocardialinfrct, fup 0.025 22 17.1 1 Diabetes w/no complications 0.025 23 4.3 1Headaches 0.020 24 9.11 1 Asthma 0.020 25 10.2 1 Hypertension 0.020 2622.11 1 Calculus of kidney and ureter 0.020 27 15.4 1 Cholelithiasis0.020 1.000

TABLE 37 9. ENDOCRINOLOGY Medical Market- Order Condition SOI MedicalCondition basket Number Number Level Short Description Weight 1 25.2 1Infertility female 0.175 2 23.10 1 Endometriosis 0.125 3 17.1 1 Diabetesw/no complications 0.125 4 17.2 1 Diabetes with ophthalmic 0.050 5 16.31 Hypothyroidism 0.075 6 16.4 1 Hyperthyroidism 0.050 7 16.2 1 Goiter0.050 8 23.7 1 Menstrual disorders 0.050 9 23.6 1 Ovarian dysfunction0.050 10 23.11 1 Ovarian cyst 0.025 11 19.4 1 Disorders of lipidmetabolism 0.050 12 19.4 2 Disorders of lipid metabolism 0.025 13 18.1 1Other endocrine disorders 0.025 14 19.6 1 Other disorders of metabolism0.025 15 18.3 1 Disorders of pituitary gland 0.025 16 18.4 1 Benign neopof pituitary gland 0.025 17 18.2 1 Disorders of adrenal gland 0.025 1810.2 1 Hypertension 0.025 1.000

TABLE 38 10. GASTROENTEROLOGY Medical Market- Order Condition SOIMedical Condition basket Number Number Level Short Description Weight 113.13 1 Noninfect gastroent & colitis 0.125 2 13.9 1 Irritable colon0.050 3 13.6 1 Gastroesophageal reflux 0.100 4 13.4 1 Other disorders ofesophagus 0.050 5 13.17 1 Benign neop colon/rectum 0.075 6 13.5 1Gastritis and duodenitis 0.075 7 13.20 1 Crohn's disease 0.075 8 13.10 1Peptic ulcer 0.075 9 13.11 1 Diverticula of intestine 0.050 10 13.21 1Gastrointestinal hemorrhage 0.050 11 13.12 1 Other diseases of intestine0.050 12 12.2 1 Hemorrhoids 0.050 13 14.2 1 Diaphragmatic hernia 0.02514 13.8 1 Dsdr stomach & duodenum 0.025 15 13.7 1 Functional digestivediseases 0.025 16 15.7 1 Hepatitis 0.020 17 15.10 1 Chronic liverdisease 0.020 18 15.9 1 Diseases of pancreas 0.020 19 15.4 1Cholelithiasis 0.020 20 36.17 1 Abdominal pain 0.020 1.000

TABLE 39 11. GENERAL SURGERY Medical Market- Order Condition SOI MedicalCondition basket Number Number Level Short Description Weight 1 14.3 1External abdominal hernias 0.125 2 15.4 1 Cholelithiasis 0.125 3 30.1 1Inflammatory disease of breast 0.075 4 30.2 1 Cystic breast disease0.050 5 30.3 1 Benign neoplasm of breast 0.050 6 12.2 1 Hemorrhoids0.050 7 29.15 1 Sebaceous cyst 0.050 8 29.18 1 Lipoma 0.050 9 13.14 1Appendicitis 0.050 10 30.8 1 Malig neop of breast, initial 0.050 1130.10 1 Malig neop of breast, fup 0.025 12 12.1 1 Anal fissure andfistula 0.050 13 13.17 1 Benign neop colon/rectum 0.025 14 13.13 1Noninfect gastroent & colitis 0.025 15 13.18 1 Intestinal obstruction0.025 16 13.12 1 Other diseases of intestine 0.025 17 29.19 1 Benignneoplasm of skin 0.025 18 12.5 1 Varicose veins lower extrem 0.025 1929.16 1 Pilonidal cyst 0.020 20 29.6 1 Skin keratoses 0.020 21 2.9 1Viral warts 0.020 22 13.30 1 Malig neop of colon, initial 0.020 23 29.261 Other malignancy of skin 0.020 1.000

TABLE 40 12. NEPHROLOGY Medical Market- Order Condition SOI MedicalCondition basket Number Number Level Short Description Weight 1 22.15 1Renal failure 0.150 2 22.15 2 Renal failure 0.075 3 17.5 1 Diabetes withrenal 0.100 4 17.5 2 Diabetes with renal 0.075 5 22.12 1Glomerulonephritis 0.075 6 10.2 1 Hypertension 0.075 7 22.9 1 Cong anomkidney and ureter 0.075 8 22.10 1 Disorders of kidney and ureter 0.075 922.17 1 Kidney transplant, follow-up 0.050 10 19.2 1 Dsdr of fluids andelectrolytes 0.050 11 22.11 1 Calculus of kidney and ureter 0.050 1219.4 1 Disorders of lipid metabolism 0.050 13 19.6 1 Other disorders ofmetabolism 0.050 14 22.3 1 Urinary tract infections 0.050 1.000

TABLE 41 13. NEUROLOGY Medical Market- Order Condition SOI MedicalCondition basket Number Number Level Short Description Weight 1 4.3 1Headaches 0.150 2 4.18 1 Seizure disorders 0.125 3 31.9 1 Low back pain0.075 4 31.8 1 Cervical spine pain 0.050 5 4.5 1 Carpal tunnel syndrome0.050 6 4.20 1 Other CNS diseases 0.075 7 4.19 1 Multiple sclerosis0.050 8 4.2 1 Peripheral neuropathy 0.050 9 4.1 1 Neuritis upper, lowerlimbs 0.050 10 6.8 1 Vertiginous syndromes 0.050 11 4.8 1 Tremordisorders 0.050 12 4.17 1 Parkinson's disease 0.025 13 11.12 1 Occulsionof cerebral 0.025 arteries 14 11.10 1 Transient cerebral ischemia 0.02515 4.21 1 Muscular dystrophies 0.025 16 4.12 1 Paralytic syndromes 0.02517 4.4 1 Disorders of cranial nerves 0.025 18 34.20 1 Sleep apnea 0.02519 4.14 1 Benign neoplasm of CNS 0.025 20 31.3 1 Other arthropathydisorders 0.025 1.000

TABLE 42 14. NEUROSURGERY Medical Market- Order Condition SOI MedicalCondition basket Number Number Level Short Description Weight 1 31.9 1Low back pain 0.200 2 31.9 2 Low back pain 0.100 3 31.8 1 Cervical spinepain 0.125 4 4.5 1 Carpal tunnel syndrome 0.075 5 4.14 1 Benign neoplasmof CNS 0.075 6 4.24 1 Malig neop brain, initial 0.075 7 18.4 1 Benignneop of pituitary gland 0.050 8 31.21 1 Fracture of vertebra 0.050 911.4 1 Concussion 0.050 10 4.20 1 Other CNS diseases 0.050 11 4.16 1Cong anomalies nerv sys 0.050 12 31.2 1 Congenital anomalies of spine0.050 13 4.4 1 Disorders of cranial nerves 0.025 14 11.10 1 Transientcerebral ischemia 0.025 1.000

TABLE 43 15. OBSTETRICS/GYNECOLOGY (OB/GYN) Medical Market- OrderCondition SOI Medical Condition basket Number Number Level ShortDescription Weight 1 26.4 1 Single newborn, normal 0.225 2 26.5 1 Singlenewborn, complicated 0.075 3 23.2 1 Cervicitis and vaginitis 0.050 423.1 1 Disorders of cervix and vagina 0.050 5 23.9 1 Benign neoplasm ofuterus 0.050 6 1.2 1 Gynecological exam 0.050 7 23.10 1 Endometriosis0.050 8 23.4 1 Other disorders of uterus 0.025 9 23.5 1 Other dsdrfemale genital org 0.050 10 23.7 1 Menstrual disorders 0.050 11 23.8 1Menopausal symptoms 0.050 12 23.11 1 Ovarian cyst 0.050 13 23.3 1Uterovaginal prolapse 0.050 14 25.2 1 Infertility female 0.025 15 26.3 1Spont and induced abortions 0.025 16 25.1 1 Contraceptive management0.025 17 30.2 1 Cystic breast disease 0.025 18 30.1 1 Inflammatorydisease of breast 0.025 19 22.3 1 Urinary tract infections 0.025 20 2.91 Viral warts 0.025 1.000

TABLE 44 16. ONCOLOGY/HEMATOLOGY Medical Market- Order Condition SOIMedical Condition basket Number Number Level Short Description Weight 130.8 1 Malig neop of breast, initial 0.075 2 30.9 1 Malig neop ofbreast, active 0.100 3 30.10 1 Malig neop of breast, fup 0.050 4 24.9 1Malig neop of prostate, active 0.075 5 24.10 1 Malig neop of prostate,inactive 0.075 6 9.19 1 Malig neop bron/lung, active 0.075 7 9.20 1Malig neop bron/lung, inactive 0.050 8 13.31 1 Malig neop of colon,active 0.025 9 13.32 1 Malig neop of colon, fup 0.025 10 20.3 1 Diseasesof white blood cells 0.075 11 20.6 1 Thrombocytopenia 0.050 12 20.5 1Aplastic anemias 0.050 13 20.4 1 Anemia disorders 0.050 14 20.2 1 Dz ofblood forming organs 0.050 15 21.6 1 Lymphoma, inactive 0.050 16 21.11 1Leukemia, inactive 0.050 17 21.8 1 Hodgkin's disease, inactive 0.050 1823.9 1 Benign neoplasm of uterus 0.025 1.000

TABLE 46 17. OPHTHALMOLOGY Medical Market- Order Condition SOI MedicalCondition basket Number Number Level Short Description Weight 1 5.17 1Cataract 0.175 2 5.17 2 Cataract 0.075 3 5.16 1 Glaucoma 0.100 4 5.16 2Glaucoma 0.050 5 5.10 1 Strabismus 0.075 6 5.20 1 Retinal detach &defects 0.050 7 5.18 1 Other retinal disorders 0.050 8 17.2 1 Diabeteswith ophthalmic 0.050 9 5.2 1 Conjunctivitis 0.050 10 5.3 1 Other dsdrof conjunctiva 0.025 11 5.4 1 Infections of the eyelids 0.025 12 5.14 1Disorders of vitreous body 0.025 13 5.6 1 Dsdr of lacrimal system 0.02514 5.15 1 Other eye disorders 0.025 15 5.7 1 Keratitis 0.025 16 5.8 1Other disorders of cornea 0.025 17 5.21 1 Blindness & visual disturb0.025 18 5.19 1 Macular degeneration 0.025 19 5.9 1 Dsdr iris andciliary body 0.025 20 5.11 1 External eye injury 0.025 21 5.13 1Internal eye injury 0.025 22 5.5 1 Disorders of eyelids 0.025 1.000

TABLE 47 18. ORAL MAXILLARY Medical Market- Order Condition SOI MedicalCondition basket Number Number Level Short Description Weight 1 8.12 1Diseases of jaw 0.125 2 8.10 1 TMJ disorder 0.125 3 8.6 1 Anomalies ofjaw size 0.125 4 8.7 1 Other dentofacial anom 0.100 5 8.4 1 Disorders ofteeth 0.100 6 8.14 1 Diseases of oral soft tissue 0.075 7 8.16 1 Jawfracture 0.075 8 8.5 1 Open wound face & mouth 0.075 9 8.13 1 Diseasesof salivary glands 0.050 10 8.15 1 Benign neop of oral cavity 0.050 118.9 1 Other dz supporting struct 0.050 12 8.2 1 Cong anomalies oralcavity 0.050 1.000

TABLE 48 19. ORTHOPEDICS Medical Market- Order Condition SOI MedicalCondition basket Number Number Level Short Description Weight 1 33.22 1Derangement of knee 0.100 2 33.21 1 Other joint derangement 0.050 3 31.41 Bursitis 0.100 4 31.4 2 Bursitis 0.025 5 31.9 1 Low back pain 0.075 631.9 2 Low back pain 0.025 7 31.8 1 Cervical spine pain 0.050 8 33.15 1Degenerative joint disease 0.075 9 32.11 1 Fracture of hand bones 0.05010 32.13 1 Fracture of radius and ulna 0.050 11 32.14 1 Fracture ofhumerus 0.050 12 33.16 1 Fracture of foot bones 0.025 13 33.17 1Fracture of ankle 0.025 14 33.19 1 Fracture of tibia and fibula 0.025 154.5 1 Carpal tunnel syndrome 0.050 16 33.9 1 Dislocation of knee 0.05017 31.12 1 Scoliosis 0.025 18 32.2 1 Sprain/strain of wrist & finger0.025 19 33.2 1 Sprain/strain of foot and ankle 0.025 20 33.3 1Sprain/strain of leg 0.020 21 4.1 1 Neuritis upper, lower limbs 0.020 2231.3 1 Other arthropathy disorders 0.020 23 32.1 1 Contusion of upperlimb 0.020 24 33.1 1 Contusion of lower limb 0.020 1.000

TABLE 49 20. OTOLARYNGOLOGY (ENT) Medical Market- Order Condition SOIMedical Condition basket Number Number Level Short Description Weight 16.5 1 Otitis media 0.150 2 7.2 1 Sinusitis 0.075 3 7.2 2 Sinusitis 0.0504 7.1 1 Rhinitis 0.075 5 9.5 1 Hypertrophy tonsils & aden 0.075 6 7.4 1Deviated nasal septum 0.075 7 6.10 1 Hearing loss 0.050 8 6.8 1Vertiginous syndromes 0.050 9 9.2 1 Dz upper respiratory tract 0.050 109.1 1 Upper respiratory infections 0.050 11 7.5 1 Nasal bone fracture0.025 12 6.1 1 Otitis externa 0.025 13 6.6 1 Dsdr of tympanic membrane0.025 14 6.7 1 Disorders of middle ear 0.025 15 6.4 1 Other disorders ofear 0.025 16 4.3 1 Headaches 0.025 17 6.2 1 Wax in ear 0.025 18 2.10 1Infectious mononucleosis 0.025 19 8.13 1 Diseases of salivary glands0.025 20 8.15 1 Benign neop of oral cavity 0.025 21 8.14 1 Diseases oforal soft tissue 0.025 22 16.2 1 Goiter 0.025 1.000

TABLE 50 21. PEDIATRICS Medical Market- Order Condition SOI MedicalCondition basket Number Number Level Short Description Weight 1 6.5 1Otitis media 0.175 2 9.1 1 Upper respiratory infections 0.125 3 7.2 1Sinusitis 0.100 4 9.4 1 Acute bronchitis 0.075 5 9.11 1 Asthma 0.050 67.1 1 Rhinitis 0.050 7 9.7 1 Pneumonia 0.050 8 13.13 1 Noninfectgastroent & colitis 0.050 9 13.3 1 Infect diarrhea/gastroenteritis 0.02510 29.9 1 Dermatitis and eczema 0.050 11 2.6 1 Other viral diseases0.025 12 5.2 1 Conjunctivitis 0.025 13 22.3 1 Urinary tract infections0.025 14 6.1 1 Otitis externa 0.025 15 36.16 1 Non-specific exanthem0.025 16 34.14 1 Personality & disturb dsdr 0.025 17 2.9 1 Viral warts0.025 18 29.7 1 Impetigo 0.025 19 29.14 1 Dermatophytoses 0.025 20 36.171 Abdominal pain 0.025 1.000

TABLE 51 22. PLASTIC SURGERY Medical Market- Order Condition SOI MedicalCondition basket Number Number Level Short Description Weight 1 30.1 1Inflammatory disease of breast 0.175 2 30.2 1 Cystic breast disease0.075 3 29.19 1 Benign neoplasm of skin 0.125 4 8.5 1 Open wound face &mouth 0.100 5 32.5 1 Open wound hand & fingers 0.075 6 6.3 1 Open woundof ear 0.025 7 4.5 1 Carpal tunnel syndrome 0.050 8 29.6 1 Skinkeratoses 0.050 9 29.26 1 Other malignancy of skin 0.050 10 21.2 1Hemangioma 0.050 11 29.15 1 Sebaceous cyst 0.050 12 29.18 1 Lipoma 0.05013 29.5 1 Other dsdr skin/subcutan tiss 0.050 14 7.4 1 Deviated nasalseptum 0.025 15 29.28 1 Malig melanoma of skin, initial 0.025 16 30.10 1Malig neop of breast, fup 0.025 1.000

TABLE 52 23. PODIATRY Medical Market- Order Condition SOI MedicalCondition basket Number Number Level Short Description Weight 1 33.14 1Hammer toe 0.125 2 33.14 2 Hammer toe 0.050 3 29.20 1 Dz of nail,excluding infections 0.100 4 31.4 1 Bursitis 0.100 5 29.10 1 Cellul &abscess, finger/toe 0.075 6 2.9 1 Viral warts 0.075 7 31.3 1 Otherarthropathy disorders 0.075 8 33.11 1 Cong deformities lower limb 0.0759 31.9 1 Low back pain 0.050 10 33.22 1 Derangement of knee 0.050 1129.14 1 Dermatophytoses 0.050 12 4.1 1 Neuritis upper, lower limbs 0.05013 33.16 1 Fracture of foot bones 0.050 14 33.15 1 Degenerative jointdisease 0.025 15 33.13 1 Benign neop of lower limb 0.025 16 29.25 1Chronic skin ulcer 0.025 1.000

TABLE 53 24. PSYCHIATRY Medical Market- Order Condition SOI MedicalCondition basket Number Number Level Short Description Weight 1 34.21 1Major depression 0.175 2 34.21 2 Major depression 0.050 3 34.14 1Personality & disturb dsdr 0.150 4 34.14 2 Personality & disturb dsdr0.050 5 34.17 1 Nonpsychotic depression 0.100 6 34.13 1 Anxietydisorders 0.075 7 34.6 1 Other neurotic disorders 0.075 8 34.24 1Bipolar depression 0.050 9 34.20 1 Sleep apnea 0.025 10 34.5 1 Insomnia0.025 11 34.18 1 Obsessive-compulsive dsdr 0.025 12 34.29 1 Alcoholdependence 0.025 13 34.30 1 Drug dependence 0.025 14 34.32 1Schizophrenia 0.025 15 34.31 1 Organic dementias 0.025 16 34.12 1 Phobicdisorders 0.025 17 34.23 1 Manic depression 0.025 18 34.15 1 Othernonorganic psychoses 0.025 19 34.25 1 Bulimia 0.025 1.000

TABLE 54 25. PSYCHOLOGY Medical Market- Order Condition SOI MedicalCondition basket Number Number Level Short Description Weight 1 34.14 1Personality & disturb dsdr 0.175 2 34.14 2 Personality & disturb dsdr0.075 3 34.21 1 Major depression 0.125 4 34.21 2 Major depression 0.0505 34.17 1 Nonpsychotic depression 0.125 6 34.13 1 Anxiety disorders0.075 7 34.6  1 Other neurotic disorders 0.075 8 34.18 1Obsessive-compulsive dsdr 0.050 9 34.29 1 Alcohol dependence 0.050 1034.30 1 Drug dependence 0.025 11 34.26 1 Anorexia nervosa 0.025 12 34.251 Bulimia 0.025 13 34.12 1 Phobic disorders 0.025 14 34.8  1 Sexualdeviations 0.025 15 34.24 1 Bipolar depression 0.025 16 34.31 1 Organicdementias 0.025 17 34.15 1 Other nonorganic psychoses 0.025 1.000

TABLE 55 26. PULMONOLOGY Medical Market- Order Condition SOI MedicalCondition basket Number Number Level Short Description Weight 1 9.14 1COPD 0.150 2 9.11 1 Asthma 0.150 3 34.20 1 Sleep apnea 0.075 4 9.10 1Chronic bronchitis 0.075 5 9.4 1 Acute bronchitis 0.050 6 9.7 1Pneumonia 0.050 7 9.3 1 Lower respiratory diseases 0.050 8 10.2 1Hypertension 0.050 9 7.2 1 Sinusitis 0.050 10 7.1 1 Rhinitis 0.050 119.9 1 Pleurisy 0.050 12 19.7 1 Cystic fibrosis 0.050 13 9.1 1 Upperrespiratory infections 0.050 14 36.18 1 Dyspnea 0.050 15 9.19 1 Maligneop bron/lung, active 0.025 16 9.20 1 Malig neop bron/lung, inactive0.025 1.000

TABLE 56 27. RHEUMATOLOGY Medical Market- Order Condition SOI MedicalCondition basket Number Number Level Short Description Weight 1 31.19 1Rheumatoid arthritis 0.175 2 31.18 1 Diffuse connective tiss dsdr 0.1503 33.15 1 Degenerative joint disease 0.125 4 31.9 1 Low back pain 0.0755 31.8 1 Cervical spine pain 0.050 6 31.3 1 Other arthropathy disorders0.050 7 31.4 1 Bursitis 0.075 8 29.23 1 Psoriasis and pityriasis 0.050 919.5 1 Gout 0.050 10 4.5 1 Carpal tunnel syndrome 0.050 11 31.14 1Osteoporosis 0.025 12 31.5 1 Other dsdr bone & cartilage 0.025 13 4.7 1Nerve root and plexus dsdr 0.025 14 11.7 1 Disorders of arteries 0.02515 19.4 1 Disorders of lipid metabolism 0.025 16 33.22 1 Derangement ofknee 0.025 1.000

TABLE 57 28. SPORTS/PHYSICAL MEDICINE Medical Market- Order ConditionSOI Medical Condition basket Number Number Level Short DescriptionWeight 1 31.4 1 Bursitis 0.175 2 31.4 2 Bursitis 0.025 3 31.9 1 Low backpain 0.100 4 31.8 1 Cervical spine pain 0.050 5 33.22 1 Derangement ofknee 0.075 6 33.15 1 Degenerative joint disease 0.075 7 33.21 1 Otherjoint derangement 0.075 8 31.3 1 Other arthropathy disorders 0.050 932.3 1 Sprain/strain of upper arm 0.075 10 32.2 1 Sprain/strain of wrist& finger 0.050 11 33.2 1 Sprain/strain of foot and ankle 0.050 12 33.3 1Sprain/strain of leg 0.050 13 33.4 1 Sprain/strain of hip and thigh0.050 14 11.4 1 Concussion 0.050 15 32.13 1 Fracture of radius and ulna0.025 16 4.5 1 Carpal tunnel syndrome 0.025 1.000

TABLE 58 29. UROLOGY Medical Market- Order Condition SOI MedicalCondition basket Number Number Level Short Description Weight 1 22.11 1Calculus of kidney and ureter 0.150 2 24.6 1 Prostatic hypertro &prostatitis 0.125 3 23.3 1 Uterovaginal prolapse 0.075 4 22.10 1Disorders of kidney and ureter 0.075 5 22.3 1 Urinary tract infections0.075 6 24.4 1 Disorders of penis 0.075 7 24.9 1 Malig neop of prostate,active 0.075 8 24.10 1 Malig neop of prostate, inactive 0.025 9 22.5 1Urethral stricture 0.050 10 24.3 1 Dsdr of male genital organs 0.050 1125.4 1 Infertility male 0.050 12 22.4 1 Urethritis 0.025 13 24.2 1Orchitis and epididymitis 0.025 14 12.4 1 Varicose veins of other sites0.025 15 22.6 1 Other disorders of bladder 0.025 16 24.1 1 Hyrocele0.025 17 14.3 1 External abdominal hernias 0.025 18 2.9 1 Viral warts0.025 1.000

TABLE 59 30. VASCULAR SURGERY Medical Market- Order Condition SOIMedical Condition basket Number Number Level Short Description Weight 114.3 1 External abdominal hernias 0.100 2 15.4 1 Cholelithiasis 0.100 330.2 1 Cystic breast disease 0.075 4 30.1 1 Inflammatory disease ofbreast 0.075 5 30.3 1 Benign neoplasm of breast 0.050 6 12.5 1 Varicoseveins lower extrem 0.075 7 11.8 1 Generalized arteriosclerosis 0.050 811.8 2 Generalized arteriosclerosis 0.025 9 13.14 1 Appendicitis 0.05010 12.3 1 Other peripheral vascular dz 0.050 11 11.12 1 Occulsion ofcerebral arteries 0.050 12 11.7 1 Disorders of arteries 0.050 13 29.18 1Lipoma 0.050 14 29.15 1 Sebaceous cyst 0.050 15 13.17 1 Benign neopcolon/rectum 0.025 16 12.6 1 Thrombophlebitis 0.025 17 29.19 1 Benignneoplasm of skin 0.025 18 12.2 1 Hemorrhoids 0.025 19 17.1 1 Diabetesw/no complications 0.025 20 17.4 1 Diabetes with circulatory 0.025 1.000

TABLE 60 31. CRITICAL CARE (INTENSIVIST) Medical Market- Order ConditionSOI Medical Condition basket Number Number Level Short DescriptionWeight 1 9.14 1 COPD 0.150 2 9.11 1 Asthma 0.150 3 34.20 1 Sleep apnea0.075 4 9.10 1 Chronic bronchitis 0.075 5 9.4 1 Acute bronchitis 0.050 69.7 1 Pneumonia 0.050 7 9.3 1 Lower respiratory diseases 0.050 8 10.2 1Hypertension 0.050 9 7.2 1 Sinusitis 0.050 10 7.1 1 Rhinitis 0.050 119.9 1 Pleurisy 0.050 12 19.7 1 Cystic fibrosis 0.050 13 9.1 1 Upperrespiratory infections 0.050 14 36.18 1 Dyspnea 0.050 15 9.19 1 Maligneop bron/lung, active 0.025 16 9.20 1 Malig neop bron/lung, inactive0.025 1.000Step 14: Perform PROVSPEC Output Process

The PROVSPEC output process involves the completion of Fields 8-10 inTable 25, Fields in the PATAN Output File. Field 8 indicates thephysician specialty. Field 9 indicates the physician marketbasket. Field10 indicates the physician aggregate grouping code number.

Step 15: Store PROSPEC Output File

The PROSPEC Output File is stored with the same fields and in the sameorder as Table 25, Fields in the PATAN Output File. However, Fields 8-10have now been completed.

Step 16: Sort PROVSPEC Output File: PROVSORT2

In an embodiment, the PROVSPEC Output File is sorted by three main sortkeys. The primary sort key is report group. The secondary sort key ismarketbasket identifier. The third sort key is physician identifier.

Step 17: Read in Episode Assignments to PROVAN from PROVSORT2

The episode assignments from PROVSORT2 are read into the physiciananalysis module (PROVAN). PROVAN produces the physician efficiencyscores and several output files at the conclusion of processing.

Step 18: Perform High Outlier Analysis

There are two high-end outlier analysis rules. Both rules are performedat the marketbasket and physician specialty level. Both rules areperformed after episodes have been assigned to individual physicians (orphysician groups, if the analysis is at the physician group levelinstead of the individual physician level).

The first high-end outlier rule is as follows. A percent of aphysician's most expensive episodes are eliminated by medical conditionand severity-of-illness (SOI) level. The user select the percent to beeliminated from the choices available for the parameterSWITCH_HIGHOUTPERCENT in the RUN.INI file (refer to Table 6, Parametersin the RUN.INI File). Episodes are removed from each medical conditionin the physician's marketbasket separately, starting with the mostexpensive episode and continuing in order of expense until the specifiedpercent of episodes is reached.

If a physician has fewer than the number of condition-specific episodesrequired to satisfy the high outlier rule described above (for example,fewer than 20 episodes when the threshold is set at 5%), then the usermay analyze the condition further, as described below under theSWITCH_HIGHOUTDIFF parameter.

In determining the number of condition-specific episodes available forthis analysis, all episodes are excluded from the count if they fallbelow the low outlier threshold set by the parameterSWITCH_LOWOUTDOLLAR, which is described in the low outliers step.

The second high-end outlier rule is as follows. The parameterSWITCH_HIGHOUTDIFF in the RUN.INI file is used to determine whether asingle episode should be removed as a high-outlier (refer to Table 6,Parameters in the RUN.INI File). This high-end outlier parameter isapplied when one high-end outlier cannot be removed under theSWITCH_HIGHOUTPERCENT parameter. The user sets the value of thisparameter to a whole number representing a percentage. If the chargesfor the most expensive episode are at least the defined percentagegreater than the charges for the next most expensive episode, the mostexpensive episode is removed as a high outlier.

For example, consider a physician whose highest upper respiratoryinfection episode charge is $500 and whose second highest upperrespiratory infection charge is $165 and SWITCH_HIGHOUTDIFF set at 200%.To be eliminated, the physician's most expensive episode must be 200% ofthe next most expensive episode. Since $500 is more than 200% of $165,the high charge episode will be removed as a high outlier. If thehigh-charge episode had been $300, it would not be removed, since $300is only 82% greater than $165.

A maximum of one episode for each medical condition in the physician'smarketbasket may be removed by this analysis. Although the user can setSWITCH_HIGHOUTDIFF to any amount, for most effective analysis, therecommended setting is between 150% and 250%.

Step 19: Perform Low Outlier Analysis

There are two low-end outlier analysis rules. Both rules are performedat the marketbasket and physician specialty level. Both rules areperformed before episodes have been assigned to individual physicians(or physician groups, if the analysis is at the physician group levelinstead of the individual physician level).

The first low-end outlier analysis is performed with respect to allepisodes by medical condition and severity-of-illness (SOI) level thatare assigned to a report group. For this analysis, all physicians areexamined within the same medical specialty and within the same AggregateReport Group.

A percent of the least expensive episodes is eliminated by medicalcondition and SOI level. The user selects the percent to be eliminatedfrom the choices available for the parameter SWITCH_LOWOUTPERCENT in theRUN.INI file (refer to Table 6, Parameters in the RUN.INI File).Episodes are removed from each medical condition separately, startingwith the least expensive episode and continuing until the specifiedpercent of episodes is reached. For example, assume there are 500episodes of upper respiratory infection (URI), SOI-1 level, assigned toa peer group of general internists, and the user selects 5% low-endoutliers. Then, the 25 lowest charge episodes (500×0.25) are removedfrom analysis.

The second low-end outlier rule is as follows. Any remainingcondition-specific episodes are eliminated with less than a definedthreshold of charges. The user sets the threshold, which can be anywhole number representing dollars in the RUN.INI file using theparameter SWITCH_LOWOUTDOLLAR (refer to Table 6, Parameters in theRUN.INI File). In the above example, assume after applying the 5%low-end outlier analysis, the user found that episodes of URI, SOI-1level remained that are less than $20. By setting the parameterSWITCH_LOWOUTDOLLAR to $20, any remaining URI, SOI-1 level episodes lessthan $20 would be removed from analysis.

Step 20: Calculate Physician Condition-Specific Episode Statistics

For condition-specific, SOI-level episodes assigned to a physician, theepisode means (averages) and standard deviations are calculated forutilization and charges in the following service and sub-servicecategories: (1) overall condition-specific, SOI-level episode duration(in days; refer to Table 61); (2) overall condition-specific, SOI-levelepisode charges (refer to Table 62); (3) service categorycondition-specific, SOI-level episode utilization (refer to Table 61);(4) service category condition-specific, SOI-level episode charges(refer to Table 62); (5) sub-service category condition-specific,SOI-level episode utilization (refer to Table 63); and (6) sub-servicecategory condition-specific, SOI-level episode charges (refer to Table64).

In an embodiment, there are 11 service category utilization fields(Fields 1-11 in Tables 61 and 62) that are set up within the servicecategory utilization section of the PATAN and PROVSPEC output displays.The system of the present invention does not break out charges forinpatient facility admissions so Field 9 is not used and contains a zeroas a placeholder (refer to Table 62).

In an embodiment, there are 21 category utilization fields (Fields 1-21in Tables 63 and 64) that are set up within the service categoryutilization section of the PATAN and PROVSPEC output displays. Thesystem of the present invention does not break out charges for inpatientfacility admissions so Field 14 is not used and contains a zero as aplaceholder (refer to Table 64).

The zero field in the service and sub-service categories for utilizationdata (Tables 61 and 63) corresponds to the average episode duration. Thezero field in the service and sub-service categories for charges (Tables62 and 64) corresponds to the average charges per episode.

It is to be understood that other statistics can be calculated forcondition-specific, SOI-level episodes assigned to a physician. In anembodiment, different service and sub-service categories may becalculated for episode utilization and charges. In an embodiment,episodes can be assigned to physician groups (and not only individualphysicians), and the physician group's episode means and standarddeviations may be calculated for utilization and charges.

TABLE 61 Service Category Fields Used for Utilization Data UtilizationField Service Category 0 Episode Duration (Days) 1 Professional Visits 2Laboratory/Pathology 3 Diagnostic Tests 4 Medical/Surgical 5Prescription Drugs 6 Inpatient Professional 7 Outpatient Facility 8Inpatient Facility Days 9 Inpatient Facility Admits 10 AlternateFacility 11 Other Medical Care

TABLE 62 Service Category Fields Used for Charge Data Charge FieldService Category 0 Overall Charges 1 Professional Visits 2 Lab/Path 3Diagnostic Tests 4 Medical/Surgical 5 Prescriptions Drugs 6 InpatientProfessional 7 Outpatient Facility 8 Inpatient Facility Days 9 [Notused] 10 Alternate Facility 11 Other Medical Care

TABLE 63 Sub-Service Category Fields Used for Utilization DataUtilization Field Sub-service category 0 Episode Duration (Days) 1Professional Visits 2 Lab 3 Pathology 4 Imaging 5 Invasive Testing 6Functional Testing 7 Medical Procedures 8 Surgical Procedures 9Prescription Drugs 10 Inpatient Professional 11 Emergency Room Facility12 Other Outpatient Facility 13 Inpatient Facility Days 14 InpatientFacility Admits 15 Alternate Facility 16 Physical Therapy 17 Dialysis 18Chemotherapy/Radiology 19 Anesthesia 20 Durable Medical Equipment 21Other Medical Care

TABLE 64 Sub-Service Category Fields Used for Charge Data Charge FieldSub-service category 0 Overall charges 1 Professional Visits 2 Lab 3Pathology 4 Imaging 5 Invasive Testing 6 Functional Testing 7 MedicalProcedures 8 Surgical Procedures 9 Prescription Drugs 10 InpatientProfessional 11 Emergency Room Facility 12 Other Outpatient Facility 13Inpatient Facility Days 14 [Not used] 15 Alternate Facility 16 PhysicalTherapy 17 Dialysis 18 Chemotherapy/Radiology 19 Anesthesia 20 DurableMedical Equipment 21 Other Medical CareStep 21: Determine Minimum Episode Number

A physician should have a minimum number of non-outlier episodes formedical conditions within a marketbasket of medical conditions. Thesystem of the present invention recognizes that a physician should havea minimum number of non-outlier episodes in each of threespecialty-specific medical conditions to receive an efficiencymeasurement score. This episode is called the N×3 rule because itrequires N episodes in each of three medical conditions.

The user specifies the number of episodes (N) using the parameterSWITCH_MINEPCOUNT in the RUN.INI file (refer to Table 6, Parameters inthe RUN.INI File). This parameter sets the requirement for the number ofepisodes a physician should treat to be included in the analysis, thusimplementing part of the N×3 rule. For example, if the N value ischanged from two to four, the rule would require four non-outlierepisodes in each of three conditions, and the rule would become, ineffect, a “4×3” rule.

In the N×3 rule, the N equals the number of episodes of a specificmedical condition a physician should treat during the study period. Theuser can change this number. The three equals the minimum number ofmedical conditions in which the physician should treat episodes. Themedical conditions need to be in the physician's marketbasket.

For example, if N in the N×3 rule is set to two, then a physician needsto have two non-outlier episodes in three medical conditions (2×3) in arespective specialty-specific marketbasket. Therefore, regardless ofspecialty type, each physician needs to have a minimum six non-outlierepisodes of care to receive an efficiency score.

Continuing our example, with N set to two episodes, and assuming aphysician meets the minimum episode number criteria in three medicalconditions (e.g., 2×3), then the following method is employed beforeformulating a weighted average treatment pattern. For a physician withless than two episodes for any medical condition in a marketbasket, thephysician-specific results are replaced with that of the peer groupresults for the medical condition of interest. For the scenario justdefined, the peer group's condition-specific results will be used whenformulating the physician's weighted average treatment pattern resultsfor at least one medical condition in the marketbasket.

Therefore, an additional rule applies when a physician has fewer thanthe required number of condition-specific episodes (as set by the valueof N). Substitute the specialty-specific, peer group results for amedical condition when a physician has less than the required number ofcondition-specific episodes.

It is to be understood that other, similar methods and rules may beemployed to ensure a physician has a minimum number of assigned,non-outlier episodes for medical conditions.

Step 22: Remove Physicians Failing Minimum Episode Number

This rule involves removing those physicians from further analysis thatdo not meet the minimum number of assigned episodes rule. For example,using the N×3 rule and assuming N is set to 2 episodes, then physicianswithout a minimum of 6 non-outlier episodes meeting the 2×3 rule areremoved from further analysis.

Step 23: Calculate Peer Group Condition-Specific Episode Statistics

Using only those episodes of care assigned to physicians meeting theminimum non-outlier episode rule (i.e., physicians that passed theminimum episode rule and, therefore, are included in further analysis),the peer group medical condition, SOI-level episode means (averages) andstandard deviations are calculated for utilization and charges. Eachepisode of care is counted once and only once in formulating the peergroup condition-specific, SOI-level means and standard deviations.

Similar to the physician-level episode statistics, the peer groupcondition-specific, SOI-level statistics are calculated for utilizationand charges using the same service and sub-service categories as definedin Tables 61-64.

For condition-specific, SOI-level episodes assigned to the peer group,the episode means (averages) and standard deviations are calculated forutilization and charges in the following service and sub-servicecategories: (1) overall condition-specific, SOI-level episode duration(in days; refer to Table 61); (2) overall condition-specific, SOI-levelepisode charges (refer to Table 62); (3) service categorycondition-specific, SOI-level episode utilization (refer to Table 61);(4) service category condition-specific, SOI-level episode charges(refer to Table 62); (5) sub-service category condition-specific,SOI-level episode utilization (refer to Table 63); and (6) sub-servicecategory condition-specific, SOI-level episode charges (refer to Table64). It is to be understood that other statistics can be calculated forthe peer group condition-specific, SOI-level episodes, and thatdifferent service and sub-service categories may be calculated forepisode utilization and charges.

Step 24: Calculate Peer Group Weighted Episode Statistics Across MedicalConditions

Each medical condition in a specialty-specific marketbasket is assigneda weight factor that reflects the importance or relevance of thatmedical condition to the marketbasket. The weight factors are used tocompute the overall marketbasket weighted mean and standard deviationacross all medical conditions in the marketbasket. The sum of the weightfactors in a marketbasket equals 1.00 (refer to the specialty-specificmarketbaskets, Tables 29-60). This step is referred to as the indirectstandardization rule.

The system of the present invention uses an indirect standardizationtechnique for weighting together the episodes within the core group ofmedical conditions. The weighted mean and standard deviation arecomputed as the sum of the condition-specific utilization or chargeamounts per episode multiplied by the weight value assigned to thatcondition in the marketbasket. Both the condition-specific means andvariances (i.e., the square of the standard deviation) are multiplied bythe weight values. The sum of all the condition-specific products is theweighted mean and standard deviation for the peer group in themarketbasket.

An example of the indirect standardization rule is presented for generalinternists. The general internist marketbasket consists of episodes in30 medical conditions, SOI-1 class only (refer to Table 30, generalinternist marketbasket). Upper respiratory infections (URIs), sinusitis,acute bronchitis, and low back pain are medical conditions within thegeneral internist marketbasket.

For simplicity, assume only four medical conditions comprise the generalinternist marketbasket: upper respiratory infections (URIs), sinusitis,acute bronchitis, and low back pain. A total of four medical conditionsin the marketbasket classes will receive a weight factor. Assume thestandardized weights are distributed as follows: URI=0.30;sinusitis=0.30; and acute bronchitis=0.20; and back pain=0.20. Theseweight factors sum to 1.00. The peer group treats a total of 4,500non-outlier episodes: 1,350 episodes of URI; 1,350 episodes ofsinusitis; 900 episodes of acute bronchitis; and 900 episodes of lowback pain.

The weighted average is now formulated for the peer group's overallepisode charges. The peer group's condition-specific means and standarddeviations (SD) are as follows: URI=$150 per episode (SD=$50);sinusitis=$200 per episode (SD=$70); acute bronchitis=$175 per episode(SD=$55); and back pain=$300 per episode (SD=$90).

Using these assumptions, the marketbasket weighted mean and standarddeviation (SD) are calculated for the general internist peer group. Theweighted overall charge mean is $200((0.30×$150)+(0.30×$200)+(0.20×$175)+(0.20×$300)). The calculation doesnot use the peer group's actual episode composition to calculate theweighted average. Instead, the predetermined standard marketbasketweights are used.

The variances are weighted together, which is the SD squared. Afteradding the variances together, the square root is performed to formulatethe weighted average SD, which is $67((0.30×$2,500)+(0.30×$4,900)+(0.20×$3,025)+(0.20×$8,100)=$4,445; and thesquare root of $4,445=$67).

Therefore, the general internist peer group's weighted overall chargemean and SD are as follows: mean=$200 per episode; SD=$67 per episode;number of episodes N=4,500.

In a similar manner, the weighted statistics are calculated for the peergroup's episode duration (in days), service category utilization andcharges (refer to Tables 61 and 62), and sub-service categoryutilization and charges (refer to Tables 63 and 64).

Step 25: Calculate Physician Weighted Episode Statistics Across MedicalConditions

For the individual physician (or alternatively, physician group), thesame indirect standardization weighting calculations are performed usingthe physician's condition-specific utilization and charges per episodeand the same specialty-specific marketbasket weights. The sum of all thecondition-specific products is the weighted mean and standard deviationresult for the physician.

Assume there continue to be only four medical conditions that comprisethe general internist marketbasket: upper respiratory infections (URIs),sinusitis, acute bronchitis, and low back pain. A total of four medicalconditions in the marketbasket classes will receive a weight factor.Also, assume the same standardized weights as for the peer group:URI=0.30; sinusitis=0.30; and acute bronchitis=0.20; and back pain=0.20.These weight factors sum to 1.00.

Without detailing the calculations here, assume the physician's weightedoverall charge mean and SD are $254 per episode and $56 per episode,respectively. The number of physician episodes (N) is 53.

In a similar manner, the weighted statistics are calculated for thephysician's episode duration, service category utilization and charges,and sub-service category utilization and charges.

Step 26: Determine Physician's Efficiency Scores

The physician's marketbasket weighted statistics are now compared tothat of the specialty-specific peer group. This comparison is moremeaningful (than just comparing treatment patterns for one medicalcondition) because the weighted statistics present a more realisticefficiency evaluation of the physician's overall work effort.

The overall efficiency score for the physician (or physician group) iscalculated by dividing the physician's weighted overall mean charges bythe peer group's weighted overall mean charges. Using the generalinternist example, the overall efficiency score equals 1.27 (or $254 perepisode/$200 per episode. The 1.27 ratio may be interpreted as follows.The efficiency of the physician's weighted average treatment pattern is27% more resource intensive than the peer group's weighted averagetreatment pattern. The general internist in the example had $54 perepisode in excess charges ($254 per episode versus the peer group of$200 per episode).

If the efficiency score is more than 1.00, then the physician'streatment pattern efficiency is more resource intensive than the peergroup's treatment pattern. On the other hand, if the efficiency score isless than 1.00, then the physician's treatment pattern efficiency isless resource intensive than the peer group's treatment pattern.

An efficiency score may be calculated for each medical condition in aspecialty-specific marketbasket. The medical condition efficiency scorefor the physician is calculated by dividing the physician'scondition-specific mean charges by the peer group's condition-specificmean charges.

An efficiency score may be calculated for each service category in anepisode of care. The overall service efficiency score for the physicianis calculated by dividing the physician's weighted service category meanutilization or charges by the peer group's weighted service categorymean utilization or charges, respectively.

The medical condition service efficiency score for a physician iscalculated by dividing the physician's condition-specific service meanutilization or charges by the peer group's condition-specific meanutilization or charges, respectively.

In addition, an efficiency score may be calculated for each sub-servicecategory in an episode of care. The overall sub-service efficiency scorefor the physician is calculated by dividing the physician's weightedsub-service category mean utilization or charges by the peer group'sweighted sub-service category mean utilization or charges, respectively.The medical condition sub-service efficiency score for a physician iscalculated by dividing the physician's condition-specific sub-servicecategory mean utilization or charges by the peer group'scondition-specific sub-service mean utilization or charges,respectively.

An efficiency score may be calculated for the duration of an episode ofcare. The overall duration efficiency score for the physician iscalculated by dividing the physician's weighted overall mean duration bythe peer group's weighted overall mean duration. A condition-specificduration efficiency score may be calculated by dividing the physician'scondition-specific mean duration by the peer group's condition-specificmean duration.

Step 27: Perform Test to Determine Whether Physician's Efficiency Scoresare Statistically Different from Peer Group

The student t-test is used to determine whether the physician's (orphysician group's) efficiency score is statistically significantlydifferent from the peer group. In the calculation, the physician'sactual number of episodes is used as well as the peer group's actualnumber of episodes. For the general internist example, the physician'snumber of episodes is N equals 53, and the peer group's number ofepisodes is N equals 4,500.

At a determined level of confidence, the physician's marketbaskettreatment pattern is determined to be statistically significantlydifferent from the peer group average. The user chooses the desiredlevel of confidence (either 0.10 level or 0.25 level) using theparameter SWITCH_CONFLEVEL in the RUN.INI file, which sets the p-valuefor statistical confidence (refer to Table 6, Parameters in the RUN.INIFile). However, different p-values may be selected other than the 0.10and 0.25 levels.

Step 28: Assign Physicians to an Interval

After receiving an efficiency score, physicians of a specific specialtytype are separated into quartiles (1, 2, 3, and 4). Quartile 1physicians use fewer medical resources to treat a marketbasket ofcondition-specific episodes as compared to their physician peer group.Quartile 2 and Quartile 3 physicians are the next quartiles ofphysicians in terms of the amount of resources used to treat the samemarketbasket of condition-specific episodes. Quartile 4 physicians usegreater medical resources to treat the same marketbasket ofcondition-specific episodes as compared to the physician peer group.

Physicians of a specific specialty type also are separated into deciles(1, 2, 3, 4, 5, 6, 7, 8, 9, and 10). Decile 1 physicians use fewermedical resources to treat a marketbasket of condition-specific episodesas compared to their physician peer group. Decile 2 through 9 physiciansare the next deciles of physicians in terms of the amount of resourcesused to treat the same marketbasket of condition-specific episodes.Decile 10 physicians use the greatest amount of medical resources totreat the same marketbasket of condition-specific episodes as comparedto the physician peer group.

The quartile and decile assignments are fields displayed on the PROVANOutput File. The embodiment recognizes that other physician intervalassignments may be used other than quartile and decile.

Step 29: Store PROVAN Output Files

The system of the present invention stores two output files at theconclusion of processing. One file is entitled the Weighted AverageResults File (default file name in RUN.INI File is Score.tab). The otherfile is entitled the Medical Condition Results File (default file namein RUN.INI File is Detail.tab).

These files are output from the PROVAN module. Table 65 provides anoverview of the two output files. The table shows that the WeightedAverage Results File produces physician-level (or physician group-level)results for the 11 service categories and 21 sub-service categories.However, the Medical Condition Results File produces physician-level (orphysician group-level) results only for the 11 service categories. Theembodiment recognizes that both PROVAN Output Files may produce resultsfor the 21 sub-service categories as well as other formulated serviceand sub-service categories.

TABLE 65 PROVAN Output Files Default 11 Service 21 Sub- File Categoryservice Descriptive Name in Level Category File Name RUN.INI Descriptionof Content Output Output Weighted Score.tab Physician-level YES YESAverage weighted average Results File marketbasket results onutilization and charges per episode of care within a marketbasket ofinterest Medical Detail.tab Physician-level YES NO Condition medicalcondition level Results File results on utilization and charges perepisode of care within a marketbasket of interestThe Weighted Average Results File presents the weighted averagespecialty-specific marketbasket results for a physician versus thecomparator peer group. The file contains one output row per physician.Fields in each row show a weighted average result for each of the 11service categories and each of the 21 sub-service categories. Fields aredelimited by tab characters and, therefore, field width is variable. Thefields in the Weighted Average Results File are divided into sections aspresented in Table 66.

TABLE 66 Sections in the Weighted Average Results File Section Title ANon-Repeated Physician Fields B Repeated Physician Fields for EachService Category C Non-Repeated Peer Group Fields D Repeated Peer GroupFields for Each Service Category E Repeated Physician Fields for EachSub-Service Category F Repeated Peer Group Fields for Each Sub-ServiceCategory

Section A contains non-repeated physician fields (16 fields). The fieldsdescribed in Section A contain physician data. Each field appears oncein the Weighted Average Results File (refer to Table 67).

Section B contains repeated physician fields for each service category(6 fields repeated 11 times). Section B lists six fields that containphysician output data at the service category level. For convenience,the six fields, taken together, are called a group. In the WeightedAverage Results File, the group of six fields listed in Section Brepeats 11 times, once for each of the service categories, in the orderlisted in Tables 61 and 62.

Section C contains non-repeated peer group fields (2 fields). The fieldsdescribed in Section C contain peer group data. Each field appears oncein the Weighted Average Results File, in the order they are listed inTable 67.

Section D contains repeated peer group fields for each service category(2 fields repeated 11 times). Section D lists two fields that containpeer group output data at the service category level. The two fields,taken together, are a group. In the Weighted Average Results File (Table67), the group of two fields listed in Section D repeats 11 times, oncefor each of the service categories in the order listed in Tables 61 and62.

Section E contains repeated physician fields for each sub-servicecategory (4 fields repeated 21 times). Section E lists four fields thatcontain physician output data at the sub-service category level. Thefour fields, taken together, are a group. In the Weighted AverageResults File, the group of four fields listed in Section E repeats 21times, once for each of the sub-service categories in the order listedin Tables 63 and 64.

Section F contains repeated peer group fields for each sub-servicecategory (2 fields repeated 21 times). Section F lists two fields thatcontain peer group output data at the sub-service category level. Thetwo fields, taken together, are a group. In the Weighted Average Resultsfile, the group of two fields listed in Section F repeats 21 times, oncefor each of the sub-service categories in the order listed in Tables 63and 64.

Table 67 presents the fields included in the Weighted Average ResultsFile, listed in the order in which they appear. In the repeated fieldsections, the asterisk (*) indicates a sequential number of the servicecategory or sub-service category number as presented in Tables 61-64.

TABLE 67 Fields in the Weighted Average Results File Field Number FieldDescriptive Name Notes Section A - Non-Repeated Physician Fields (16fields) 1 Physician ID The unique physician ID for each profiledphysician, Field name: ProvID as defined in the input files. 2 PhysicianSpecialty Number The specialty number, as defined in the data Fieldname: ProvSpec mapping section. 3 Physician marketbasket number Themarketbasket number, as defined in the data Field name: MktBasketmapping section. 4 Aggregate group number The aggregate group number, asdefined in the Field name: AggGroup grouping structure table. 5 Pass NxNrule 1 = The physician passed the Nx3 rule Field name: PassNxN 0 = Thephysician failed the Nx3 rule 6 Quartile number The quartile number ofthe physician based on Field name: Quartile overall charge efficiency. 1= lowest relative resource intensity 4 = highest relative resourceintensity 7 Decile number The decile number of the physician based onoverall Field name: Decile charge efficiency. 1 = lowest relativeresource intensity 10 = highest relative resource intensity 8 Episodevolume category Indicates relative volume of total episodes for theField name: epcountbin physician. 1 = 25 or fewer episodes, 2 = 26 to 50episodes, 3 = greater than 50 episodes. 9 Physician episode count Thetotal number of episodes for the physician, after Field name:provider_episode_count outliers are removed. 10 Peer group episode countThe total number of episodes forming the peer Field name:peergroup_episode_count group, after outliers are removed. 11 Physicianweighted average episode Weighted average episode duration in days.duration Field name: Prov_MBCCatUtl0 12 Physician relative efficiencyscore based Score as compared to peer group based on relative on episodeduration weighted average episode duration in days. Field name:Prov_ScoreCatUtl0 13 Physician episode duration t-test 1 = result ofphysician t-test for average weighted statistical significance indicatorepisode duration is statistically significant at the Field name:Prov_TScoreCatUtl_sigdiff0 selected confidence level. 0 = notstatistically significant at selected confidence level. 14 Physicianoverall weighted average Overall weighted average episode charges indollars, episode charges across all service categories. Field name:Prov_MBCCatChg0 15 Physician overall relative efficiency score Score ascompared to peer group based on overall based on episode chargesrelative weighted average episode charges in Field name:Prov_ScoreCatChg0 dollars. 16 Physician episode charges t-test 1 =result of physician t-test for average weighted statistical significanceindicator episode charges is statistically significant at the Fieldname: selected confidence level. Prov_TScoreCatChg_sigdiff0 0 = notstatistically significant at selected confidence level. Section B -Repeated Physician Fields for Each Service Category (6 fields repeated11 times) 1 Physician weighted average per episode Weighted average perepisode utilization for the utilization for the service category servicecategory (service category 8 contains Field name: Prov_MBCCatUtl*inpatient days per episode, service category 9 contains inpatient admitsper episode) 2 Physician relative efficiency score based Score ascompared to peer group based on relative on per episode utilization forthe service weighted average per episode utilization for the categoryservice category Field name: Prov_ScoreCatUtl* 3 Physician per-episodeutilization t-test 1 = result of physician t-test for average weightedstatistical significance indicator utilization for the service categoryis statistically Field name: Prov_TScoreCatUtl_sigdiff* significant atthe selected confidence level. 0 = not statistically significant atselected confidence level. 4 Physician weighted average episode Weightedaverage episode charges in dollars, for the charges for the servicecategory service category Field name: Prov_MBCCatChg* 5 Physicianrelative efficiency score based Score as compared to peer group based onrelative on episode charges for the service weighted average episodecharges in dollars, for the category service category Field name:Prov_ScoreCatChg* 6 Physician episode charges t-test 1 = result ofphysician t-test for average weighted statistical significance indicatorfor the episode charges for the service category is service categorystatistically significant at the selected confidence Field name: level.Prov_TScoreCatChg_sigdiff* 0 = not statistically significant at selectedconfidence level. Section C - Non-Repeated Peer Group Fields (2 fields)1 Peer Group overall weighted average Peer Group overall weightedaverage episode episode duration duration in days Field name:Peer_MBCCatUtl0 2 Peer Group overall weighted average Peer Group overallweighted average episode episode charges in dollars charges in dollars,across all service categories Field name: Peer_MBCCatChg0 (Section D)Repeated Peer Group Fields for Each Service Category (2 fields repeated11 times) 1 Peer Group weighted average episode Peer Group weightedaverage episode utilization for utilization for the service category theservice category Field name: Peer_MBCCatUtl* 2 Peer Group weightedaverage episode Peer Group weighted average episode charges in chargesin dollars for the service dollars for the service category categoryField name: Peer_MBCCatChg* Section E - Repeated Physician Fields forEach Sub-Service Category (4 fields repeated 21 times) 1 Physicianweighted average per episode Weighted average per episode utilizationfor the sub- utilization for the sub-service category service category(sub-service category 13 contains Field name: Prov_MBCSubUtl* inpatientdays per episode, sub-service category 14 contains inpatient admits perepisode) 2 Physician per-episode utilization t-test 1 = result ofphysician t-test for average weighted statistical significance indicatorutilization for the sub-service category is statistically Field name:Prov_TScoreSubUtl_sigdiff* significant at the selected confidence level.0 = not statistically significant at selected confidence level. 3Physician weighted average episode Weighted average episode charges indollars, for the charges for the sub-service category sub-servicecategory Field name: Prov_MBCSubChg* 4 Physician episode charges t-test1 = result of physician t-test for average weighted statisticalsignificance indicator for the episode charges for the sub-servicecategory is sub-service category statistically significant at theselected confidence Field name: level. Prov_TScoreSubChg_sigdiff* 0 =not statistically significant at selected confidence level. Section F -Repeated Peer Group Fields for Each Sub-Service Category (2 fieldsrepeated 21 times) 1 Peer Group weighted average episode Peer Groupweighted average episode utilization for utilization for thesub-category the sub-service category Field name: Peer_MBCSubUtl* 2 PeerGroup weighted average episode Peer Group weighted average episodecharges in charges in dollars for the sub-service dollars for thesub-service category category Field name: Peer_MBCSubChg*

The Medical Condition Results File presents the specialty-specificmedical condition results for a physician versus the comparator peergroup. Table 65 shows that medical condition average utilization andcharge results are available for each of the 11 service categoriestracked in the system of the present invention (e.g., lab/pathservices).

The Medical Condition Results File contains rows of data on medicalconditions for each physician. There are up to 36 rows per physician (upto 35 medical conditions, plus the weighted average row). These rows ofdata are identified by the Marketbasket Condition Number field (Field 11in Table 68).

The overall weighted average information has been carried over for eachphysician from the Weighted Average Results File and reported in theMedical Conditions Results file as well. For each physician, theweighted average output row is identified in the Marketbasket ConditionNumber field with the number “0”. The rows of medical conditioninformation for each physician begin with row “1” and continue untilthere is a row for the weighted average of each medical condition in thephysician's specialty marketbasket.

Table 68 presents the fields included in the Medical Condition ResultsFile, listed in the order in which they appear. In the repeated fieldsections, the asterisk (*) indicates a sequential number of the servicecategory number as presented in Tables 61 and 62.

TABLE 68 Fields in the Medical Condition Results File Field Number FieldDescriptive Name Notes Section A - Fundamental Information (19 fields) 1Physician ID The unique physician ID for each profiled physician, asdefined Field name: ProvID in the input files. 2 Physician SpecialtyNumber The specialty number, as defined in the data mapping section.Field name: ProvSpec 3 Physician marketbasket The marketbasket number,as defined in the data mapping number section. Field name: MktBasket 4Aggregate group number The aggregate group number, as defined in thegrouping Field name: AggGroup structure table. 5 Pass NxN rule 1 = Thephysician passed the Nx3 rule Field name: PassNxN 0 = The physicianfailed the Nx3 rule 6 Quartile number The quartile number of thephysician based on overall charge Field name: Quartile efficiency. 1 =lowest relative resource intensity 4 = highest relative resourceintensity 7 Decile number The decile number of the physician based onoverall charge Field name: Decile efficiency. 1 = lowest relativeresource intensity 10 = highest relative resource intensity 8 Episodevolume category Indicates relative volume of total episodes for thephysician. Field name: epcountbin 1 = 25 or fewer episodes 2 = 26 to 50episodes 3 = greater than 50 episodes 9 Physician episode count Thetotal number of episodes for the physician, after outliers Field name:are removed. provider_episode_count 10 Peer group episode count Thetotal number of episodes forming the peer group, after Field name:outliers are removed. peergroup_episode_count 11 Marketbasket conditionThe sequential number of the condition within the number marketbasket,as defined in the market conditions table which Field name: MBConditionis specified by the RUN.INI parameter FILE_MBCONDITIONS. 12 Physicianaverage episode Average episode duration in days. For the “0” row, thisfield duration contains the weighted average episode duration in days.For all Field name: other rows, this field contains the average medicalcondition Prov_MBCatUtl0 duration in days. 13 Physician relativeefficiency Score as compared to peer group based on relative averagescore based on episode episode duration in days. duration Field name:Prov_ScoreCatUtl0 14 Physician t-score for average t-test score resultas compared to peer group on relative episode duration average episodeduration in days. Field name: Prov_TScoreCatUtl0 15 Physician episodeduration t- 1 = result of physician t-test for average episode durationis test statistical significance statistically significant at theselected confidence level. indicator 0 = not statistically significantat selected confidence level. Field name: Prov_TScoreCatUtl_sigdiff0 16Physician average episode Average episode charges in dollars, across allservice charges categories. For the “0” row, this field contains theweighted Field name: overall average episode charges. For all otherrows, this field Prov_MBCCatChg0 contains the overall average medicalcondition charges per episode. 17 Physician relative efficiency Score ascompared to peer group based on relative average score based on episodeepisode charges in dollars. charges Field name: Prov_ScoreCatChg0 18Physician t-score for average t-test score result as compared to peergroup on relative episode charges average episode charges in dollars.Field name: Prov_TScoreCatChg0 19 Physician episode charges t- 1 =result of physician t-test for average episode charges is teststatistical significance statistically significant at the selectedconfidence level. indicator 0 = not statistically significant atselected confidence level. Field name: Prov_TScoreCatChg_sigdiff0Section B - Repeated Physician Fields for Each Service Category (8fields repeated 11 times) 1 Physician average per Average per episodeutilization for the service category episode utilization for the(service category 8 contains inpatient days per episode, servicecategory service category 9 contains inpatient admits per episode). ForField name: the “0” row, this field contains the weighted averageutilization Prov_MBCCatUtl* for the service category. For all otherrows, this field contains the average medical condition utilization forthe service category. 2 Physician relative efficiency Score as comparedto peer group based on relative average score based on per episode perepisode utilization for the service category utilization for the servicecategory Field name: Prov_ScoreCatUtl* 3 Physician t-score for thet-test score result as compared to peer group on relative servicecategory utilization average per episode utilization for the servicecategory Field name: Prov_TScoreCatUtl* 4 Physician per-episode 1 =result of physician t-test for average utilization for the utilizationt-test statistical service category is statistically significant at theselected significance indicator confidence level. Field name: 0 = notstatistically significant at selected confidence level.Prov_TScoreCatUtl_sigdiff* 5 Physician average episode Average episodecharges in dollars, for the service category. charges for the serviceFor the “0” row, this field contains the weighted average categorycharges for the service category. For all other rows, this field Fieldname: contains the average medical condition charges for the serviceProv_MBCCatChg* category. 6 Physician relative efficiency Score ascompared to peer group based on relative average score based on episodeepisode charges in dollars, for the service category charges for theservice category Field name: Prov_ScoreCatChg* 7 Physician t-score foraverage t-test score result as compared to peer group on relativeepisode charges for the average episode charges in dollars for theservice category service category Field name: Prov_TScoreCatChg* 8Physician episode charges t- 1 = result of physician t-test for averageepisode charges for test statistical significance the service categoryis statistically significant at the selected indicator for the serviceconfidence level. category 0 = not statistically significant at selectedconfidence level. Field name: Prov_TScoreCatChg_sigdiff* Section C -Non-Repeated Peer Group Fields (2 fields) 1 Peer Group average episodePeer Group average episode duration in days. For the “0” row, durationthis field contains the weighted average episode duration in Field name:days. For all other rows, this field contains the average medicalPeer_MBCCatUtl0 condition duration in days. 2 Peer Group average episodePeer Group average episode charges in dollars, across all charges indollars service categories. For the “0” row, this field contains theField name: weighted overall average episode charges. For all otherrows, Peer_MBCCatChg0 this field contains the overall average medicalcondition charges per episode. Section D - Repeated Peer Group Fieldsfor Each Service Category (2 fields repeated 11 times) 1 Peer Groupaverage episode Peer Group average episode utilization for the servicecategory utilization for the service (service category 8 containsinpatient days per episode, category service category 9 containsinpatient admits per episode). For Field name: the “0” row, this fieldcontains the weighted average utilization Peer_MBCCatUtl* for theservice category. For all other rows, this field contains the averagemedical condition utilization for the service category.. 2 Peer Groupaverage episode Peer Group average episode charges in dollars for theservice charges in dollars for the category. For the “0” row, this fieldcontains the weighted service category average charges for the servicecategory. For all other rows, Field name: this field contains theaverage medical condition charges for Peer_MBCCatChg* the servicecategory.Step 30: Produce Reports

The open structure of the PROVAN Output Files allows the user to producemany types of physician-level (or physician group-level) reports.

The system of the present invention also produces reports using thePROVAN Output Files that provide the user with physician-level (orphysician group-level) information to help understand what underlies thephysician's overall efficiency score. These reports are called thePractitioner Efficiency Measurement Reports.

Practitioner Efficiency Measurement Reports provide statistical analysisat the overall weighted average level that identifies physician chargesand utilization that are significantly different from peer groupresults. The Reports may also provide statistical analysis at themedical condition level.

For each of the 31 specialty types with a marketbasket of medicalconditions, there is a corresponding Practitioner Efficiency MeasurementReport. The Practitioner Efficiency Measurement Reports present thedetails behind a practitioner's efficiency measurement score.

The Practitioner Efficiency Measurement Report consists of two reportsfor each of the 31 practitioner specialty types. Report 1 is entitledAverage Charges per Episode of Care. This report presents a physician'soverall weighted average charges per episode as well as the overallweighted average charge per episode for the peer group. These two chargevalues form the foundation for the practitioner's efficiency score.Report 2 is entitled Average Utilization per Episode of Care. Thisreport presents a physician's corresponding weighted average utilizationpatterns per episode as well as the peer group's weighted averageutilization patterns per episode.

FIG. 8 presents a detailed description of Report 1, the Average Chargesper Episode of Care. Results from a general internist are compared to apeer group of general internists.

The headings at the top of the FIG. 8 report are as follows. Thepractitioner name is the name of the physician receiving an efficiencyscore. Specialty type refers to the specialty of the physician receivingan efficiency score. The attached general internist's specialty type isshown as General Internist. The practitioner ID is the uniqueidentification number that is assigned to the physician receiving anefficiency score. The system of the present invention organizes theinformation output and reports based on aggregate group name. Aggregategroup name is the name of the aggregate group relevant to the currentreport. For example, if a comparison is made on the basis of geographicregions, the aggregate group name might represent a specific regiondefined by identifying individual zip codes. The quartile is assigned toeach physician after each specialty-specific physician in a regionreceives an efficiency score. The decile is assigned to each physicianafter each specialty-specific physician in a region receives anefficiency score. The efficiency score for a physician is calculated bydividing the physician's weighted average overall mean charge by thepeer group's weighted average overall mean charge. The attached generalinternist's efficiency score is 1.32, indicating that the internist'streatment pattern efficiency is 32% more resource intensive than thepeer group's practice. The significant difference allows the user toobserve whether the physician's efficiency score is statisticallysignificantly different from the peer group average. ‘Yes’ means thephysician's efficiency score is significantly different from the peergroup's efficiency score. The user may employ two different levels ofconfidence (0.10 confidence level and 0.25 confidence level). Theattached general internist's efficiency score is statisticallysignificantly different than the peer group—indicated by the Yes in thisfield.

The body of the report headings are as follows. The medical conditionname is the condition within a specialty-specific marketbasket. For thegeneral internist marketbasket, this column lists the conditionsgenerally treated by general internists. The peer group weighted averageis at the top of the medical condition column. This row presents thepeer group's weighted average charge per episode results. For example,the general internist peer group's overall weighted average charges are$205 per episode (see Column 4 of the FIG. 8 report). The practitionerweighted average row is directly under the peer group weighted averagerow, and entitled “Practitioner Weighted Avg.” This row presents eachphysician's weighted average charge per episode results. For example,the general internist's overall weighted average charges are $269 perepisode (see Column 4 of the FIG. 8 report). The star next to the $269per episode indicates that the weighted average results arestatistically significantly different (p<0.25) from the peer group'sweighted average results.

The SOI column presents the severity-of-illness (SOI) of the episodesbeing examined for a medical condition. There are up to three SOI levelsfor each medical condition, with SOI-1 being the least severe (routine,noncomplicated), and SOI-3 being the most severe. The episode countcolumn presents the number of eligible episodes being examined for thepeer group and the physician. For the general internist peer group,there are 46,656 eligible episodes. For the general internist physician,there are 217 eligible episodes. The general internist's 217 eligibleepisode count is the sum of the condition-specific episodes listed inthis column. The Report shows the general internist treated 43 episodesof hypertension, 23 episodes of diabetes with no complications, 3episodes of diabetes with circulatory involvement, 26 episodes ofdisorders of lipid metabolism, etc.).

The average charge per episode column presents the overall weightedaverage charge per episode results for the specialty-specific peergroup. For example, the general internist peer group's overall weightedaverage charges are $205 per episode (see Column 4 of the FIG. 8report). Directly under the peer group weighted average row is thephysician's weighted average charge per episode. For the generalinternist, the overall weighted average charges are $269 per episode.The star next to the physician's $269 per episode indicates that theoverall weighted average results are statistically significantlydifferent (p<0.25) from the peer group's weighted average results.

The average charge per episode column is followed by service categoriesrelated to charges. The sum of these service category columns equals theoverall average charge per episode. The service category report headingsare as follows. There are five professional outpatient and ambulatoryservices columns that present professional outpatient and ambulatorycharges. The services are physician-related and are not facility-billedservices. The first column is professional visits (prof visits). Thiscolumn presents the average charges per episode for professional visitsincurred in the physician office, clinic, or outpatient department of ahospital. The second column is diagnostic tests (diag tests). Thiscolumn presents the average charges per episode for diagnostic testsincurred in the physician office, clinic, outpatient department of ahospital, or surgicenter. Diagnostic tests represent imaging tests(X-rays, CAT scans, MRIs, etc.), functional tests (EKGs,echocardiograms, etc.), and invasive tests. The third column islaboratory and pathology (lab/path). This column presents the averagecharges per episode for laboratory and pathology services incurred inthe physician office, clinic, outpatient department of a hospital, orsurgicenter. The fourth column is medical and surgical procedures(med/surg). This column presents the average charges per episode formedical and surgical procedures incurred in the physician office,clinic, outpatient department of a hospital, or surgicenter. The fifthcolumn is prescription drugs (Rx). This column presents the averagecharges per episode for outpatient and ambulatory prescription drugs.

There is one professional inpatient services column. Thisservice-related column presents professional inpatient services. Theseservices are physician related, and not facility billed services. Thiscolumn presents the average charges per episode for all inpatientprofessional services.

There is one outpatient facility column and one inpatient facilitycolumn. These service-related columns present facility services. Theseservices are facility-related and are not professional-billed services.The facility outpatient services (outpt facility) column presents theaverage charges per episode for all outpatient facility servicesincurred in an outpatient department of a hospital or surgicenter. Thefacility inpatient admissions (hosp inpt admits) column presents theaverage charges per episode for all hospital inpatient facilityservices.

There is one alternative care site services column. This service-relatedcolumn presents facility services incurred in skilled nursing facilitiesand halfway homes. These services are facility-related and are notprofessional-billed services. This column presents the average chargesper episode for skilled nursing facility and halfway home services.

There is one other medical services column. This service-related columnpresents other professional medical services. These services arephysician-related and are not facility-billed services. The othermedical services (other med) column presents the average charges perepisode for other medical services incurred in the physician office,clinic, outpatient department of a hospital, and dialysis center. Othermedical services include physical therapy, chiropractic services (otherthan professional visits), chemotherapy and radiation, dental, durablemedical equipment, and ambulance services.

FIG. 9 presents a detailed description of Report 2, the AverageUtilization per Episode of Care. Results are observed from an actualgeneral internist as compared to a peer group of general internists.

The headings at the top of the FIG. 9 report are the same as for Report1, Average Charges per Episode (refer to FIG. 8).

The body of the report headings are as follows. The medical conditionname is the condition within a specialty-specific marketbasket. For thegeneral internist marketbasket, this column lists the conditionsgenerally treated by general internists. The peer group weighted averageis at the top of the medical condition column. This row presents thepeer group's weighted average utilization per episode results. Theservice categories present the peer group's corresponding averageutilization per episode to the Report 1 defined average charges perepisode. The practitioner weighted average row is directly under thepeer group weighted average row is a row entitled Practitioner WeightedAverage. This row presents each physician's weighted average utilizationper episode results. The service category columns present thephysician's corresponding average utilization per episode to the Report1 defined average charges per episode. The star next to a physician'saverage utilization per episode result indicates that weighted averageresults are statistically significantly different (p<0.25) from the peergroup's weighted average results.

The SOI column presents the severity-of-illness (SOI) of the episodesbeing examined for a medical condition. There are up to three SOI levelsfor each medical condition, with SOI-1 being the least severe (routine,noncomplicated), and SOI-3 being the most severe. The episode countcolumn presents the number of eligible episodes being examined for thepeer group and the physician. For the general internist peer group,there are 46,656 eligible episodes; and for the general internistphysician, there are 217 eligible episodes.

The average episode duration (days) column presents the weighted averageepisode duration per episode results for the specialty-specific peergroup. For example, the general internist peer group's weighted averageduration is 122.8 days per episode (see Column 4). Directly under thepeer group weighted average row is the physician's weighted averageduration per episode. For the general internist physician, the overallweighted average duration is 123.6 days per episode. There is no starnext to the physician's 123.6 days per episode. This indicates that theweighted average duration results are not statistically significantlydifferent (p<0.25) from the peer group's weighted average durationresults. Column 4 also presents the average duration per episode foreach medical condition treated by the general internist physician. Forinstance, the general internist treated SOI-1 hypertension for anaverage 180.0 days per episode, SOI-1 low back pain for 29.4 days perepisode, and acute bronchitis for 1.2 days per episode.

The average episode duration column is followed by 11 service categoriesrelated to utilization. The service category report headings are asfollows. There are five professional outpatient and ambulatory servicescolumns that present the physician's corresponding average utilizationper episode to the Report 1 defined average charges per episode. Theservices are physician related, and not facility billed services. Thefirst column is professional visits (prof visits). This column presentsthe average number of visits per episode for professional visitsincurred in the physician office, clinic, or outpatient department of ahospital. The numerator unit is visits. The second column is diagnostictests (diag tests). This column presents the average number ofdiagnostic tests per episode for diagnostic tests incurred in thephysician office, clinic, outpatient department of a hospital, orsurgicenter. The numerator unit is services or tests. The third columnis laboratory and pathology (lab/path). This column presents the averagenumber of lab/path services per episode for laboratory and pathologyservices incurred in the physician office, clinic, outpatient departmentof a hospital, or surgicenter. The numerator unit is services. Thefourth column is medical and surgical procedures (med/surg). This columnpresents the average number of med/surg procedures per episode formedical and surgical procedures incurred in the physician office,clinic, outpatient department of a hospital, or surgicenter. Thenumerator unit is services or procedures. The fifth column isprescription drugs (Rx). This column presents the average number ofprescription drug fills per episode for outpatient and ambulatoryprescription drugs. The numerator unit is prescription drug fills.

There is one professional inpatient services column. Thisservice-related column presents professional inpatient services. Thiscolumn presents the physician's corresponding average inpatientprofessional services to the Report 1 defined average charges perepisode. These services are physician related, and not facility billedservices. Professional inpatient services (prof inpt): This columnpresents the average professional services per episode for all inpatientprofessional services. The numerator unit is services.

There are three facility services columns (one outpatient facility andtwo inpatient facility). These service-related columns present thefacility services. The columns present the facility's correspondingaverage utilization per episode to the Report 1 defined average chargesper episode. These services are facility related, and not professionalbilled services. The facility outpatient visits (outpt facility) columnpresents the average visits per episode for all outpatient facilityservices incurred in an outpatient department of a hospital orsurgicenter. The numerator unit is visits. The facility inpatientadmissions (hosp inpt admits) column presents the average number ofadmissions per episode for all hospital inpatient facility services. Thenumerator unit is admissions. The facility inpatient days (hosp inptdays) column presents the average number of inpatient days per episodefor all hospital inpatient facility services. The numerator unit ishospital inpatient days.

There is one alternative care site services column. This service-relatedcolumn presents facility services incurred in skilled nursing facilitiesand halfway homes. This column presents the facility's correspondingaverage services per episode to the Report 1 defined average charges perepisode. These services are facility related, and not professionalbilled services. The alternative sites (altern sites) column presentsthe average services per episode for all skilled nursing facility andhalfway home services. The numerator unit is services.

There is one other medical services column. This service-related columnpresents other professional medical services. This column presents thephysician's corresponding average services per episode to the Report 1defined average charges per episode. These services are physicianrelated, and not facility billed services. The numerator unit isservices.

While various embodiments for physician efficiency measurement andpatient health risk stratification has been described and illustrated indetail, it is to be understood that various modifications can be made toembodiments of the present invention without departing from the spiritthereof.

What is claimed is:
 1. A healthcare analytics computer system forstatistical analysis of medical care information for a medical careprovider efficiency measurement, said healthcare analytics computersystem comprising a memory device for storing data and a processor incommunication with said memory device, said processor programmed to:receive a plurality of scores defining an efficiency of care whereineach of the plurality of scores is associated with one of a plurality ofphysician identifiers identifying one of a plurality of physicians;receive a plurality of episodes of care records, wherein each of theplurality of episodes of care records is associated with one of theplurality of physician identifiers identifying one of the plurality ofassociated physicians; receive a plurality of patient treatmentinformation data, wherein each of the plurality of patient treatmentinformation data includes associated claim characteristics associatedwith a particular episode of care record, wherein the associated claimcharacteristics are a subset of a plurality of claim characteristics,wherein the plurality of claim characteristics includes a medicalcondition, a severity of illness classification, an average charge perepisode of the medical condition at the severity of illnessclassification for a plurality of service categories, and an averageutilization per episode of the medical condition at the severity ofillness classification for the plurality of service categories, andwherein the average charge per episode and the average utilization perepisode are weighted according to a predetermined relevance of theassociated medical condition in a practice area associated with theplurality of physicians; determine a relationship score between each ofthe plurality of claim characteristics and score calculations byperforming a statistical analysis using the plurality of scores, theplurality of episode of care records, and the plurality of patienttreatment information data; identify at least one of the plurality ofclaim characteristics for at least one of the physicians as having anassociated relationship score exceeding a minimum threshold; and reportthe identified at least one claim characteristic as a driver ofefficiency for the at least one of the physicians.
 2. The healthcareanalytics computer system of claim 1, wherein said processor is furtherconfigured to: receive a plurality of input files defining theassociation between each of the plurality of episodes of care recordsand each of the plurality of patient treatment information data; andlink each of the plurality of episodes of care records with theassociated patient treatment information data based on the plurality ofinput files.
 3. The healthcare analytics computer system of claim 2,wherein each of the plurality of input files includes a structured datarelationship between each of the plurality of episodes of care recordsand each of the plurality of patient treatment information data.
 4. Thehealthcare analytics computer system of claim 1, wherein said processoris further configured to: identify a behavior adjustment associated witheach of the efficiency drivers; and recommend the plurality of behavioradjustments based on each identified efficiency driver.
 5. Thehealthcare analytics computer system of claim 1, wherein said processoris further configured to: receive with the plurality of scores, theplurality of episode of care records, and the plurality of patienttreatment information data, an associated geographic identifier; anddetermine the relationship score for each of the associated geographicidentifiers.
 6. The healthcare analytics computer system of claim 1,wherein said processor is further configured to: receive the pluralityof scores, the plurality of episode of care records, and the pluralityof patient treatment information data for a plurality of physicianpractice areas; and determine the relationship score for each of theassociated physician practice areas.
 7. The healthcare analyticscomputer system of claim 1, wherein said processor is further configuredto: identify a minimum threshold for episodes of care records; filterthe plurality of episodes of care records based on the identifiedminimum threshold; and determine a filtered relationship score that isbased on only episodes of care records that satisfy the identifiedminimum threshold.
 8. The healthcare analytics computer system of claim1, wherein said processor is further configured to: determine therelationship score by performing a Pearson's correlation analysis. 9.The healthcare analytics computer system of claim 1, wherein saidprocessor is further configured to: receive a plurality of input filesdefining the association between each of the plurality of episodes ofcare records and each of the plurality of patient treatment informationdata, each of the plurality of input files having a hierarchicalstructure including at least four different record types; and flattenthe hierarchical structure of the plurality of input files to generatethe plurality of patient treatment information data, such that theplurality of patient treatment information data includes only one recordtype, wherein a CPU processing time of said processor reading theflattened plurality of patient treatment information data issignificantly reduced relative to a CPU processing time for theplurality of input files.
 10. The healthcare analytics computer systemof claim 1, wherein said processor is further configured to: calculatethe plurality of scores defining the efficiency of care based on theplurality of episodes of care records, wherein the score for each of thephysicians is calculated utilizing a subset of medical conditionsclinically related to that physician's specialty type, the subsetincluding the medical conditions most commonly treated by thatphysician's specialty type, and wherein each medical condition includedin the subset of medical conditions is associated with theseverity-of-illness classification, the severity of illnessclassification representing a severity level from a plurality ofseverity levels for the corresponding medical condition, each of thesubset of medical conditions weighted by a factor representing aprevalence of the corresponding medical condition relative to othermedical conditions included within the subset.
 11. Acomputer-implemented method for statistical analysis of medical careinformation for a medical care provider efficiency measurement, saidmethod implemented by a healthcare analytics computer system comprisinga memory device for storing data and a processor in communication withthe memory device, said method comprising: receiving a plurality ofscores defining an efficiency of care wherein each of the plurality ofscores is associated with one of a plurality of physician identifiersidentifying one of a plurality of physicians; receiving a plurality ofepisodes of care records, wherein each of the plurality of episodes ofcare records is associated with one of the plurality of physicianidentifiers identifying one of the plurality of associated physicians;receiving a plurality of patient treatment information data, whereineach of the plurality of patient treatment information data includesassociated claim characteristics associated with a particular episode ofcare record, wherein the associated claim characteristics are a subsetof a plurality of claim characteristics, wherein the plurality of claimcharacteristics includes a medical condition, a severity of illnessclassification, an average charge per episode of the medical conditionat the severity of illness classification for a plurality of servicecategories, and an average utilization per episode of the medicalcondition at the severity of illness classification for the plurality ofservice categories, and wherein the average charge per episode and theaverage utilization per episode are weighted according to apredetermined relevance of the associated medical condition in apractice area associated with the plurality of physicians; determining arelationship score between each of the plurality of claimcharacteristics and score calculations by performing a statisticalanalysis using the plurality of scores, the plurality of episode of carerecords, and the plurality of patient treatment information data;identifying at least one of the plurality of claim characteristics forat least one of the physicians as having an associated relationshipscore exceeding a minimum threshold; and reporting the identified atleast one claim characteristic as a driver of efficiency for the atleast one of the physicians.
 12. The method of claim 11, furthercomprising: receiving a plurality of input files defining theassociation between each of the plurality of episodes of care recordsand each of the plurality of patient treatment information data; andlinking each of the plurality of episodes of care records with theassociated patient treatment information data based on the plurality ofinput files.
 13. The method of claim 12, wherein each of the pluralityof input files includes a structured data relationship between each ofthe plurality of episodes of care records and each of the plurality ofpatient treatment information data.
 14. The method of claim 11, furthercomprising: identifying a behavior adjustment associated with each ofthe efficiency drivers; and recommending the plurality of behavioradjustments based on each identified efficiency driver.
 15. The methodof claim 11, further comprising: receiving with the plurality of scores,the plurality of episode of care records, and the plurality of patienttreatment information data, an associated geographic identifier; anddetermining the relationship score for each of the associated geographicidentifiers.
 16. The method of claim 11, further comprising: receivingthe plurality of scores, the plurality of episode of care records, andthe plurality of patient treatment information data for a plurality ofphysician practice areas; and determining the relationship score foreach of the associated physician practice areas.
 17. The method of claim11, further comprising: identifying a minimum threshold for episodes ofcare records; filtering the plurality of episodes of care records basedon the identified minimum threshold; and determining a filteredrelationship score that is based on only episodes of care records thatsatisfy the identified minimum threshold.
 18. The method of claim 11,further comprising: determining the relationship score by performing aPearson's correlation analysis.
 19. A computer-readable storage device,having processor-executable instructions embodied thereon, forstatistical analysis of medical care information for a medical careprovider efficiency measurement using a healthcare analytics computersystem, wherein the healthcare analytics computer system includes atleast one processor and a memory device coupled to the processor,wherein, when executed by the healthcare analytics computer system, theprocessor-executable instructions cause the healthcare analyticscomputer system to: receive a plurality of scores defining an efficiencyof care wherein each of the plurality of scores is associated with oneof a plurality of physician identifiers identifying one of a pluralityof physicians; receive a plurality of episodes of care records, whereineach of the plurality of episodes of care records is associated with oneof the plurality of physician identifiers identifying one of theplurality of associated physicians; receive a plurality of patienttreatment information data, wherein each of the plurality of patienttreatment information data includes associated claim characteristicsassociated with a particular episode of care record, wherein theassociated claim characteristics are a subset of a plurality of claimcharacteristics, wherein the plurality of claim characteristics includesa medical condition, a severity of illness classification, an averagecharge per episode of the medical condition at the severity of illnessclassification for a plurality of service categories, and an averageutilization per episode of the medical condition at the severity ofillness classification for the plurality of service categories, andwherein the average charge per episode and the average utilization perepisode are weighted according to a predetermined relevance of theassociated medical condition in a practice area associated with theplurality of physicians; determine a relationship score between each ofthe plurality of claim characteristics and score calculations byperforming a statistical analysis using the plurality of scores, theplurality of episode of care records, and the plurality of patienttreatment information data; identify at least one of the plurality ofclaim characteristics for at least one of the physicians as having anassociated relationship score exceeding a minimum threshold; and reportthe identified at least one claim characteristic as a driver ofefficiency for the at least one of the physicians.
 20. Thecomputer-readable storage device of claim 19, wherein theprocessor-executable instructions cause the healthcare analyticscomputer system to: receive a plurality of input files defining theassociation between each of the plurality of episodes of care recordsand each of the plurality of patient treatment information data; andlink each of the plurality of episodes of care records with theassociated patient treatment information data based on the plurality ofinput files.
 21. The computer-readable storage device of claim 20,wherein the processor-executable instructions cause the healthcareanalytics computer system to: identify a behavior adjustment associatedwith each of the efficiency drivers; and recommend the plurality ofbehavior adjustments based on each identified efficiency driver.
 22. Thecomputer-readable storage device of claim 19, wherein theprocessor-executable instructions cause the healthcare analyticscomputer system to: receive with the plurality of scores, the pluralityof episode of care records, and the plurality of patient treatmentinformation data, an associated geographic identifier; and determine therelationship score for each of the associated geographic identifiers.23. The computer-readable storage device of claim 19, wherein theprocessor-executable instructions cause the healthcare analyticscomputer system to: receive the plurality of scores, the plurality ofepisode of care records, and the plurality of patient treatmentinformation data for a plurality of physician practice areas; anddetermine the relationship score for each of the associated physicianpractice areas.
 24. The computer-readable storage device of claim 19,wherein the processor-executable instructions cause the healthcareanalytics computer system to: identify a minimum threshold for episodesof care records; filter the plurality of episodes of care records basedon the identified minimum threshold; and determine a filteredrelationship score that is based on only episodes of care records thatsatisfy the identified minimum threshold.
 25. The computer-readablestorage device of claim 19, wherein the processor-executableinstructions cause the healthcare analytics computer system to:determine the relationship score by performing a Pearson's correlationanalysis.
 26. The computer-readable storage device of claim 19, whereinthe processor-executable instructions cause the healthcare analyticscomputer system to: identify a minimum threshold for episodes of carerecords; filter the plurality of episodes of care records based on theidentified minimum threshold; and determine a filtered relationshipscore that is based on only episodes of care records that satisfy theidentified minimum threshold.